har.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# To do linear algebra\n",
    "import numpy as np\n",
    "from numpy import pi\n",
    "\n",
    "# To create plots\n",
    "from matplotlib.colors import rgb2hex\n",
    "from matplotlib.cm import get_cmap\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.axes import Axes\n",
    "# To create nicer plots\n",
    "import seaborn as sns\n",
    "\n",
    "# To create interactive plots\n",
    "from plotly.offline import init_notebook_mode, iplot\n",
    "import plotly.graph_objs as go\n",
    "init_notebook_mode(connected=True)\n",
    "\n",
    "# To get new datatypes and functions\n",
    "from collections import Counter\n",
    "from cycler import cycler\n",
    "\n",
    "from scipy.stats import norm,skew, probplot\n",
    "from scipy.optimize import curve_fit\n",
    "\n",
    "from sklearn.preprocessing import StandardScaler, LabelEncoder\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.manifold import TSNE\n",
    "\n",
    "from lightgbm import LGBMClassifier\n",
    "\n",
    "from time import time\n",
    "\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.discriminant_analysis import QuadraticDiscriminantAnalysis\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn import preprocessing\n",
    "from sklearn.linear_model import LinearRegression, LogisticRegression\n",
    "from sklearn.ensemble import ExtraTreesClassifier\n",
    "from sklearn.feature_selection import SelectFromModel\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.model_selection import StratifiedKFold\n",
    "from sklearn.feature_selection import RFECV\n",
    "from sklearn.feature_selection import RFE\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.feature_selection import VarianceThreshold\n",
    "from sklearn.pipeline import make_pipeline\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.metrics import confusion_matrix\n",
    "import scikitplot as skplt\n",
    "import itertools\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#load dataset\n",
    "train_data = pd.read_csv('/home/siddharth/Desktop/train.csv')\n",
    "test_data = pd.read_csv('/home/siddharth/Desktop/test.csv')\n",
    "\n",
    "train_data['Data'] = 'Train'\n",
    "test_data['Data'] = 'Test'\n",
    "\n",
    "tt_data = pd.concat([train_data,test_data], axis = 0).reset_index(drop = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Check null values\n",
    "train_data.isnull().values.any()\n",
    "test_data.isnull().values.any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "tt_data['subject'] = '#' + tt_data['subject'].astype(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10299, 564)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tt_data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['tBodyAcc-mean()-X', 'tBodyAcc-mean()-Y', 'tBodyAcc-mean()-Z',\n",
       "       'tBodyAcc-std()-X', 'tBodyAcc-std()-Y', 'tBodyAcc-std()-Z',\n",
       "       'tBodyAcc-mad()-X', 'tBodyAcc-mad()-Y', 'tBodyAcc-mad()-Z',\n",
       "       'tBodyAcc-max()-X', 'tBodyAcc-max()-Y', 'tBodyAcc-max()-Z',\n",
       "       'tBodyAcc-min()-X', 'tBodyAcc-min()-Y', 'tBodyAcc-min()-Z',\n",
       "       'tBodyAcc-sma()', 'tBodyAcc-energy()-X', 'tBodyAcc-energy()-Y',\n",
       "       'tBodyAcc-energy()-Z', 'tBodyAcc-iqr()-X', 'tBodyAcc-iqr()-Y',\n",
       "       'tBodyAcc-iqr()-Z', 'tBodyAcc-entropy()-X', 'tBodyAcc-entropy()-Y',\n",
       "       'tBodyAcc-entropy()-Z', 'tBodyAcc-arCoeff()-X,1',\n",
       "       'tBodyAcc-arCoeff()-X,2', 'tBodyAcc-arCoeff()-X,3',\n",
       "       'tBodyAcc-arCoeff()-X,4', 'tBodyAcc-arCoeff()-Y,1',\n",
       "       'tBodyAcc-arCoeff()-Y,2', 'tBodyAcc-arCoeff()-Y,3',\n",
       "       'tBodyAcc-arCoeff()-Y,4', 'tBodyAcc-arCoeff()-Z,1',\n",
       "       'tBodyAcc-arCoeff()-Z,2', 'tBodyAcc-arCoeff()-Z,3',\n",
       "       'tBodyAcc-arCoeff()-Z,4', 'tBodyAcc-correlation()-X,Y',\n",
       "       'tBodyAcc-correlation()-X,Z', 'tBodyAcc-correlation()-Y,Z',\n",
       "       'tGravityAcc-mean()-X', 'tGravityAcc-mean()-Y',\n",
       "       'tGravityAcc-mean()-Z', 'tGravityAcc-std()-X',\n",
       "       'tGravityAcc-std()-Y', 'tGravityAcc-std()-Z',\n",
       "       'tGravityAcc-mad()-X', 'tGravityAcc-mad()-Y',\n",
       "       'tGravityAcc-mad()-Z', 'tGravityAcc-max()-X',\n",
       "       'tGravityAcc-max()-Y', 'tGravityAcc-max()-Z',\n",
       "       'tGravityAcc-min()-X', 'tGravityAcc-min()-Y',\n",
       "       'tGravityAcc-min()-Z', 'tGravityAcc-sma()',\n",
       "       'tGravityAcc-energy()-X', 'tGravityAcc-energy()-Y',\n",
       "       'tGravityAcc-energy()-Z', 'tGravityAcc-iqr()-X',\n",
       "       'tGravityAcc-iqr()-Y', 'tGravityAcc-iqr()-Z',\n",
       "       'tGravityAcc-entropy()-X', 'tGravityAcc-entropy()-Y',\n",
       "       'tGravityAcc-entropy()-Z', 'tGravityAcc-arCoeff()-X,1',\n",
       "       'tGravityAcc-arCoeff()-X,2', 'tGravityAcc-arCoeff()-X,3',\n",
       "       'tGravityAcc-arCoeff()-X,4', 'tGravityAcc-arCoeff()-Y,1',\n",
       "       'tGravityAcc-arCoeff()-Y,2', 'tGravityAcc-arCoeff()-Y,3',\n",
       "       'tGravityAcc-arCoeff()-Y,4', 'tGravityAcc-arCoeff()-Z,1',\n",
       "       'tGravityAcc-arCoeff()-Z,2', 'tGravityAcc-arCoeff()-Z,3',\n",
       "       'tGravityAcc-arCoeff()-Z,4', 'tGravityAcc-correlation()-X,Y',\n",
       "       'tGravityAcc-correlation()-X,Z', 'tGravityAcc-correlation()-Y,Z',\n",
       "       'tBodyAccJerk-mean()-X', 'tBodyAccJerk-mean()-Y',\n",
       "       'tBodyAccJerk-mean()-Z', 'tBodyAccJerk-std()-X',\n",
       "       'tBodyAccJerk-std()-Y', 'tBodyAccJerk-std()-Z',\n",
       "       'tBodyAccJerk-mad()-X', 'tBodyAccJerk-mad()-Y',\n",
       "       'tBodyAccJerk-mad()-Z', 'tBodyAccJerk-max()-X',\n",
       "       'tBodyAccJerk-max()-Y', 'tBodyAccJerk-max()-Z',\n",
       "       'tBodyAccJerk-min()-X', 'tBodyAccJerk-min()-Y',\n",
       "       'tBodyAccJerk-min()-Z', 'tBodyAccJerk-sma()',\n",
       "       'tBodyAccJerk-energy()-X', 'tBodyAccJerk-energy()-Y',\n",
       "       'tBodyAccJerk-energy()-Z', 'tBodyAccJerk-iqr()-X',\n",
       "       'tBodyAccJerk-iqr()-Y', 'tBodyAccJerk-iqr()-Z',\n",
       "       'tBodyAccJerk-entropy()-X', 'tBodyAccJerk-entropy()-Y',\n",
       "       'tBodyAccJerk-entropy()-Z', 'tBodyAccJerk-arCoeff()-X,1',\n",
       "       'tBodyAccJerk-arCoeff()-X,2', 'tBodyAccJerk-arCoeff()-X,3',\n",
       "       'tBodyAccJerk-arCoeff()-X,4', 'tBodyAccJerk-arCoeff()-Y,1',\n",
       "       'tBodyAccJerk-arCoeff()-Y,2', 'tBodyAccJerk-arCoeff()-Y,3',\n",
       "       'tBodyAccJerk-arCoeff()-Y,4', 'tBodyAccJerk-arCoeff()-Z,1',\n",
       "       'tBodyAccJerk-arCoeff()-Z,2', 'tBodyAccJerk-arCoeff()-Z,3',\n",
       "       'tBodyAccJerk-arCoeff()-Z,4', 'tBodyAccJerk-correlation()-X,Y',\n",
       "       'tBodyAccJerk-correlation()-X,Z', 'tBodyAccJerk-correlation()-Y,Z',\n",
       "       'tBodyGyro-mean()-X', 'tBodyGyro-mean()-Y', 'tBodyGyro-mean()-Z',\n",
       "       'tBodyGyro-std()-X', 'tBodyGyro-std()-Y', 'tBodyGyro-std()-Z',\n",
       "       'tBodyGyro-mad()-X', 'tBodyGyro-mad()-Y', 'tBodyGyro-mad()-Z',\n",
       "       'tBodyGyro-max()-X', 'tBodyGyro-max()-Y', 'tBodyGyro-max()-Z',\n",
       "       'tBodyGyro-min()-X', 'tBodyGyro-min()-Y', 'tBodyGyro-min()-Z',\n",
       "       'tBodyGyro-sma()', 'tBodyGyro-energy()-X', 'tBodyGyro-energy()-Y',\n",
       "       'tBodyGyro-energy()-Z', 'tBodyGyro-iqr()-X', 'tBodyGyro-iqr()-Y',\n",
       "       'tBodyGyro-iqr()-Z', 'tBodyGyro-entropy()-X',\n",
       "       'tBodyGyro-entropy()-Y', 'tBodyGyro-entropy()-Z',\n",
       "       'tBodyGyro-arCoeff()-X,1', 'tBodyGyro-arCoeff()-X,2',\n",
       "       'tBodyGyro-arCoeff()-X,3', 'tBodyGyro-arCoeff()-X,4',\n",
       "       'tBodyGyro-arCoeff()-Y,1', 'tBodyGyro-arCoeff()-Y,2',\n",
       "       'tBodyGyro-arCoeff()-Y,3', 'tBodyGyro-arCoeff()-Y,4',\n",
       "       'tBodyGyro-arCoeff()-Z,1', 'tBodyGyro-arCoeff()-Z,2',\n",
       "       'tBodyGyro-arCoeff()-Z,3', 'tBodyGyro-arCoeff()-Z,4',\n",
       "       'tBodyGyro-correlation()-X,Y', 'tBodyGyro-correlation()-X,Z',\n",
       "       'tBodyGyro-correlation()-Y,Z', 'tBodyGyroJerk-mean()-X',\n",
       "       'tBodyGyroJerk-mean()-Y', 'tBodyGyroJerk-mean()-Z',\n",
       "       'tBodyGyroJerk-std()-X', 'tBodyGyroJerk-std()-Y',\n",
       "       'tBodyGyroJerk-std()-Z', 'tBodyGyroJerk-mad()-X',\n",
       "       'tBodyGyroJerk-mad()-Y', 'tBodyGyroJerk-mad()-Z',\n",
       "       'tBodyGyroJerk-max()-X', 'tBodyGyroJerk-max()-Y',\n",
       "       'tBodyGyroJerk-max()-Z', 'tBodyGyroJerk-min()-X',\n",
       "       'tBodyGyroJerk-min()-Y', 'tBodyGyroJerk-min()-Z',\n",
       "       'tBodyGyroJerk-sma()', 'tBodyGyroJerk-energy()-X',\n",
       "       'tBodyGyroJerk-energy()-Y', 'tBodyGyroJerk-energy()-Z',\n",
       "       'tBodyGyroJerk-iqr()-X', 'tBodyGyroJerk-iqr()-Y',\n",
       "       'tBodyGyroJerk-iqr()-Z', 'tBodyGyroJerk-entropy()-X',\n",
       "       'tBodyGyroJerk-entropy()-Y', 'tBodyGyroJerk-entropy()-Z',\n",
       "       'tBodyGyroJerk-arCoeff()-X,1', 'tBodyGyroJerk-arCoeff()-X,2',\n",
       "       'tBodyGyroJerk-arCoeff()-X,3', 'tBodyGyroJerk-arCoeff()-X,4',\n",
       "       'tBodyGyroJerk-arCoeff()-Y,1', 'tBodyGyroJerk-arCoeff()-Y,2',\n",
       "       'tBodyGyroJerk-arCoeff()-Y,3', 'tBodyGyroJerk-arCoeff()-Y,4',\n",
       "       'tBodyGyroJerk-arCoeff()-Z,1', 'tBodyGyroJerk-arCoeff()-Z,2',\n",
       "       'tBodyGyroJerk-arCoeff()-Z,3', 'tBodyGyroJerk-arCoeff()-Z,4',\n",
       "       'tBodyGyroJerk-correlation()-X,Y',\n",
       "       'tBodyGyroJerk-correlation()-X,Z',\n",
       "       'tBodyGyroJerk-correlation()-Y,Z', 'tBodyAccMag-mean()',\n",
       "       'tBodyAccMag-std()', 'tBodyAccMag-mad()', 'tBodyAccMag-max()',\n",
       "       'tBodyAccMag-min()', 'tBodyAccMag-sma()', 'tBodyAccMag-energy()',\n",
       "       'tBodyAccMag-iqr()', 'tBodyAccMag-entropy()',\n",
       "       'tBodyAccMag-arCoeff()1', 'tBodyAccMag-arCoeff()2',\n",
       "       'tBodyAccMag-arCoeff()3', 'tBodyAccMag-arCoeff()4',\n",
       "       'tGravityAccMag-mean()', 'tGravityAccMag-std()',\n",
       "       'tGravityAccMag-mad()', 'tGravityAccMag-max()',\n",
       "       'tGravityAccMag-min()', 'tGravityAccMag-sma()',\n",
       "       'tGravityAccMag-energy()', 'tGravityAccMag-iqr()',\n",
       "       'tGravityAccMag-entropy()', 'tGravityAccMag-arCoeff()1',\n",
       "       'tGravityAccMag-arCoeff()2', 'tGravityAccMag-arCoeff()3',\n",
       "       'tGravityAccMag-arCoeff()4', 'tBodyAccJerkMag-mean()',\n",
       "       'tBodyAccJerkMag-std()', 'tBodyAccJerkMag-mad()',\n",
       "       'tBodyAccJerkMag-max()', 'tBodyAccJerkMag-min()',\n",
       "       'tBodyAccJerkMag-sma()', 'tBodyAccJerkMag-energy()',\n",
       "       'tBodyAccJerkMag-iqr()', 'tBodyAccJerkMag-entropy()',\n",
       "       'tBodyAccJerkMag-arCoeff()1', 'tBodyAccJerkMag-arCoeff()2',\n",
       "       'tBodyAccJerkMag-arCoeff()3', 'tBodyAccJerkMag-arCoeff()4',\n",
       "       'tBodyGyroMag-mean()', 'tBodyGyroMag-std()', 'tBodyGyroMag-mad()',\n",
       "       'tBodyGyroMag-max()', 'tBodyGyroMag-min()', 'tBodyGyroMag-sma()',\n",
       "       'tBodyGyroMag-energy()', 'tBodyGyroMag-iqr()',\n",
       "       'tBodyGyroMag-entropy()', 'tBodyGyroMag-arCoeff()1',\n",
       "       'tBodyGyroMag-arCoeff()2', 'tBodyGyroMag-arCoeff()3',\n",
       "       'tBodyGyroMag-arCoeff()4', 'tBodyGyroJerkMag-mean()',\n",
       "       'tBodyGyroJerkMag-std()', 'tBodyGyroJerkMag-mad()',\n",
       "       'tBodyGyroJerkMag-max()', 'tBodyGyroJerkMag-min()',\n",
       "       'tBodyGyroJerkMag-sma()', 'tBodyGyroJerkMag-energy()',\n",
       "       'tBodyGyroJerkMag-iqr()', 'tBodyGyroJerkMag-entropy()',\n",
       "       'tBodyGyroJerkMag-arCoeff()1', 'tBodyGyroJerkMag-arCoeff()2',\n",
       "       'tBodyGyroJerkMag-arCoeff()3', 'tBodyGyroJerkMag-arCoeff()4',\n",
       "       'fBodyAcc-mean()-X', 'fBodyAcc-mean()-Y', 'fBodyAcc-mean()-Z',\n",
       "       'fBodyAcc-std()-X', 'fBodyAcc-std()-Y', 'fBodyAcc-std()-Z',\n",
       "       'fBodyAcc-mad()-X', 'fBodyAcc-mad()-Y', 'fBodyAcc-mad()-Z',\n",
       "       'fBodyAcc-max()-X', 'fBodyAcc-max()-Y', 'fBodyAcc-max()-Z',\n",
       "       'fBodyAcc-min()-X', 'fBodyAcc-min()-Y', 'fBodyAcc-min()-Z',\n",
       "       'fBodyAcc-sma()', 'fBodyAcc-energy()-X', 'fBodyAcc-energy()-Y',\n",
       "       'fBodyAcc-energy()-Z', 'fBodyAcc-iqr()-X', 'fBodyAcc-iqr()-Y',\n",
       "       'fBodyAcc-iqr()-Z', 'fBodyAcc-entropy()-X', 'fBodyAcc-entropy()-Y',\n",
       "       'fBodyAcc-entropy()-Z', 'fBodyAcc-maxInds-X', 'fBodyAcc-maxInds-Y',\n",
       "       'fBodyAcc-maxInds-Z', 'fBodyAcc-meanFreq()-X',\n",
       "       'fBodyAcc-meanFreq()-Y', 'fBodyAcc-meanFreq()-Z',\n",
       "       'fBodyAcc-skewness()-X', 'fBodyAcc-kurtosis()-X',\n",
       "       'fBodyAcc-skewness()-Y', 'fBodyAcc-kurtosis()-Y',\n",
       "       'fBodyAcc-skewness()-Z', 'fBodyAcc-kurtosis()-Z',\n",
       "       'fBodyAcc-bandsEnergy()-1,8', 'fBodyAcc-bandsEnergy()-9,16',\n",
       "       'fBodyAcc-bandsEnergy()-17,24', 'fBodyAcc-bandsEnergy()-25,32',\n",
       "       'fBodyAcc-bandsEnergy()-33,40', 'fBodyAcc-bandsEnergy()-41,48',\n",
       "       'fBodyAcc-bandsEnergy()-49,56', 'fBodyAcc-bandsEnergy()-57,64',\n",
       "       'fBodyAcc-bandsEnergy()-1,16', 'fBodyAcc-bandsEnergy()-17,32',\n",
       "       'fBodyAcc-bandsEnergy()-33,48', 'fBodyAcc-bandsEnergy()-49,64',\n",
       "       'fBodyAcc-bandsEnergy()-1,24', 'fBodyAcc-bandsEnergy()-25,48',\n",
       "       'fBodyAcc-bandsEnergy()-1,8.1', 'fBodyAcc-bandsEnergy()-9,16.1',\n",
       "       'fBodyAcc-bandsEnergy()-17,24.1', 'fBodyAcc-bandsEnergy()-25,32.1',\n",
       "       'fBodyAcc-bandsEnergy()-33,40.1', 'fBodyAcc-bandsEnergy()-41,48.1',\n",
       "       'fBodyAcc-bandsEnergy()-49,56.1', 'fBodyAcc-bandsEnergy()-57,64.1',\n",
       "       'fBodyAcc-bandsEnergy()-1,16.1', 'fBodyAcc-bandsEnergy()-17,32.1',\n",
       "       'fBodyAcc-bandsEnergy()-33,48.1', 'fBodyAcc-bandsEnergy()-49,64.1',\n",
       "       'fBodyAcc-bandsEnergy()-1,24.1', 'fBodyAcc-bandsEnergy()-25,48.1',\n",
       "       'fBodyAcc-bandsEnergy()-1,8.2', 'fBodyAcc-bandsEnergy()-9,16.2',\n",
       "       'fBodyAcc-bandsEnergy()-17,24.2', 'fBodyAcc-bandsEnergy()-25,32.2',\n",
       "       'fBodyAcc-bandsEnergy()-33,40.2', 'fBodyAcc-bandsEnergy()-41,48.2',\n",
       "       'fBodyAcc-bandsEnergy()-49,56.2', 'fBodyAcc-bandsEnergy()-57,64.2',\n",
       "       'fBodyAcc-bandsEnergy()-1,16.2', 'fBodyAcc-bandsEnergy()-17,32.2',\n",
       "       'fBodyAcc-bandsEnergy()-33,48.2', 'fBodyAcc-bandsEnergy()-49,64.2',\n",
       "       'fBodyAcc-bandsEnergy()-1,24.2', 'fBodyAcc-bandsEnergy()-25,48.2',\n",
       "       'fBodyAccJerk-mean()-X', 'fBodyAccJerk-mean()-Y',\n",
       "       'fBodyAccJerk-mean()-Z', 'fBodyAccJerk-std()-X',\n",
       "       'fBodyAccJerk-std()-Y', 'fBodyAccJerk-std()-Z',\n",
       "       'fBodyAccJerk-mad()-X', 'fBodyAccJerk-mad()-Y',\n",
       "       'fBodyAccJerk-mad()-Z', 'fBodyAccJerk-max()-X',\n",
       "       'fBodyAccJerk-max()-Y', 'fBodyAccJerk-max()-Z',\n",
       "       'fBodyAccJerk-min()-X', 'fBodyAccJerk-min()-Y',\n",
       "       'fBodyAccJerk-min()-Z', 'fBodyAccJerk-sma()',\n",
       "       'fBodyAccJerk-energy()-X', 'fBodyAccJerk-energy()-Y',\n",
       "       'fBodyAccJerk-energy()-Z', 'fBodyAccJerk-iqr()-X',\n",
       "       'fBodyAccJerk-iqr()-Y', 'fBodyAccJerk-iqr()-Z',\n",
       "       'fBodyAccJerk-entropy()-X', 'fBodyAccJerk-entropy()-Y',\n",
       "       'fBodyAccJerk-entropy()-Z', 'fBodyAccJerk-maxInds-X',\n",
       "       'fBodyAccJerk-maxInds-Y', 'fBodyAccJerk-maxInds-Z',\n",
       "       'fBodyAccJerk-meanFreq()-X', 'fBodyAccJerk-meanFreq()-Y',\n",
       "       'fBodyAccJerk-meanFreq()-Z', 'fBodyAccJerk-skewness()-X',\n",
       "       'fBodyAccJerk-kurtosis()-X', 'fBodyAccJerk-skewness()-Y',\n",
       "       'fBodyAccJerk-kurtosis()-Y', 'fBodyAccJerk-skewness()-Z',\n",
       "       'fBodyAccJerk-kurtosis()-Z', 'fBodyAccJerk-bandsEnergy()-1,8',\n",
       "       'fBodyAccJerk-bandsEnergy()-9,16',\n",
       "       'fBodyAccJerk-bandsEnergy()-17,24',\n",
       "       'fBodyAccJerk-bandsEnergy()-25,32',\n",
       "       'fBodyAccJerk-bandsEnergy()-33,40',\n",
       "       'fBodyAccJerk-bandsEnergy()-41,48',\n",
       "       'fBodyAccJerk-bandsEnergy()-49,56',\n",
       "       'fBodyAccJerk-bandsEnergy()-57,64',\n",
       "       'fBodyAccJerk-bandsEnergy()-1,16',\n",
       "       'fBodyAccJerk-bandsEnergy()-17,32',\n",
       "       'fBodyAccJerk-bandsEnergy()-33,48',\n",
       "       'fBodyAccJerk-bandsEnergy()-49,64',\n",
       "       'fBodyAccJerk-bandsEnergy()-1,24',\n",
       "       'fBodyAccJerk-bandsEnergy()-25,48',\n",
       "       'fBodyAccJerk-bandsEnergy()-1,8.1',\n",
       "       'fBodyAccJerk-bandsEnergy()-9,16.1',\n",
       "       'fBodyAccJerk-bandsEnergy()-17,24.1',\n",
       "       'fBodyAccJerk-bandsEnergy()-25,32.1',\n",
       "       'fBodyAccJerk-bandsEnergy()-33,40.1',\n",
       "       'fBodyAccJerk-bandsEnergy()-41,48.1',\n",
       "       'fBodyAccJerk-bandsEnergy()-49,56.1',\n",
       "       'fBodyAccJerk-bandsEnergy()-57,64.1',\n",
       "       'fBodyAccJerk-bandsEnergy()-1,16.1',\n",
       "       'fBodyAccJerk-bandsEnergy()-17,32.1',\n",
       "       'fBodyAccJerk-bandsEnergy()-33,48.1',\n",
       "       'fBodyAccJerk-bandsEnergy()-49,64.1',\n",
       "       'fBodyAccJerk-bandsEnergy()-1,24.1',\n",
       "       'fBodyAccJerk-bandsEnergy()-25,48.1',\n",
       "       'fBodyAccJerk-bandsEnergy()-1,8.2',\n",
       "       'fBodyAccJerk-bandsEnergy()-9,16.2',\n",
       "       'fBodyAccJerk-bandsEnergy()-17,24.2',\n",
       "       'fBodyAccJerk-bandsEnergy()-25,32.2',\n",
       "       'fBodyAccJerk-bandsEnergy()-33,40.2',\n",
       "       'fBodyAccJerk-bandsEnergy()-41,48.2',\n",
       "       'fBodyAccJerk-bandsEnergy()-49,56.2',\n",
       "       'fBodyAccJerk-bandsEnergy()-57,64.2',\n",
       "       'fBodyAccJerk-bandsEnergy()-1,16.2',\n",
       "       'fBodyAccJerk-bandsEnergy()-17,32.2',\n",
       "       'fBodyAccJerk-bandsEnergy()-33,48.2',\n",
       "       'fBodyAccJerk-bandsEnergy()-49,64.2',\n",
       "       'fBodyAccJerk-bandsEnergy()-1,24.2',\n",
       "       'fBodyAccJerk-bandsEnergy()-25,48.2', 'fBodyGyro-mean()-X',\n",
       "       'fBodyGyro-mean()-Y', 'fBodyGyro-mean()-Z', 'fBodyGyro-std()-X',\n",
       "       'fBodyGyro-std()-Y', 'fBodyGyro-std()-Z', 'fBodyGyro-mad()-X',\n",
       "       'fBodyGyro-mad()-Y', 'fBodyGyro-mad()-Z', 'fBodyGyro-max()-X',\n",
       "       'fBodyGyro-max()-Y', 'fBodyGyro-max()-Z', 'fBodyGyro-min()-X',\n",
       "       'fBodyGyro-min()-Y', 'fBodyGyro-min()-Z', 'fBodyGyro-sma()',\n",
       "       'fBodyGyro-energy()-X', 'fBodyGyro-energy()-Y',\n",
       "       'fBodyGyro-energy()-Z', 'fBodyGyro-iqr()-X', 'fBodyGyro-iqr()-Y',\n",
       "       'fBodyGyro-iqr()-Z', 'fBodyGyro-entropy()-X',\n",
       "       'fBodyGyro-entropy()-Y', 'fBodyGyro-entropy()-Z',\n",
       "       'fBodyGyro-maxInds-X', 'fBodyGyro-maxInds-Y',\n",
       "       'fBodyGyro-maxInds-Z', 'fBodyGyro-meanFreq()-X',\n",
       "       'fBodyGyro-meanFreq()-Y', 'fBodyGyro-meanFreq()-Z',\n",
       "       'fBodyGyro-skewness()-X', 'fBodyGyro-kurtosis()-X',\n",
       "       'fBodyGyro-skewness()-Y', 'fBodyGyro-kurtosis()-Y',\n",
       "       'fBodyGyro-skewness()-Z', 'fBodyGyro-kurtosis()-Z',\n",
       "       'fBodyGyro-bandsEnergy()-1,8', 'fBodyGyro-bandsEnergy()-9,16',\n",
       "       'fBodyGyro-bandsEnergy()-17,24', 'fBodyGyro-bandsEnergy()-25,32',\n",
       "       'fBodyGyro-bandsEnergy()-33,40', 'fBodyGyro-bandsEnergy()-41,48',\n",
       "       'fBodyGyro-bandsEnergy()-49,56', 'fBodyGyro-bandsEnergy()-57,64',\n",
       "       'fBodyGyro-bandsEnergy()-1,16', 'fBodyGyro-bandsEnergy()-17,32',\n",
       "       'fBodyGyro-bandsEnergy()-33,48', 'fBodyGyro-bandsEnergy()-49,64',\n",
       "       'fBodyGyro-bandsEnergy()-1,24', 'fBodyGyro-bandsEnergy()-25,48',\n",
       "       'fBodyGyro-bandsEnergy()-1,8.1', 'fBodyGyro-bandsEnergy()-9,16.1',\n",
       "       'fBodyGyro-bandsEnergy()-17,24.1',\n",
       "       'fBodyGyro-bandsEnergy()-25,32.1',\n",
       "       'fBodyGyro-bandsEnergy()-33,40.1',\n",
       "       'fBodyGyro-bandsEnergy()-41,48.1',\n",
       "       'fBodyGyro-bandsEnergy()-49,56.1',\n",
       "       'fBodyGyro-bandsEnergy()-57,64.1',\n",
       "       'fBodyGyro-bandsEnergy()-1,16.1',\n",
       "       'fBodyGyro-bandsEnergy()-17,32.1',\n",
       "       'fBodyGyro-bandsEnergy()-33,48.1',\n",
       "       'fBodyGyro-bandsEnergy()-49,64.1',\n",
       "       'fBodyGyro-bandsEnergy()-1,24.1',\n",
       "       'fBodyGyro-bandsEnergy()-25,48.1', 'fBodyGyro-bandsEnergy()-1,8.2',\n",
       "       'fBodyGyro-bandsEnergy()-9,16.2',\n",
       "       'fBodyGyro-bandsEnergy()-17,24.2',\n",
       "       'fBodyGyro-bandsEnergy()-25,32.2',\n",
       "       'fBodyGyro-bandsEnergy()-33,40.2',\n",
       "       'fBodyGyro-bandsEnergy()-41,48.2',\n",
       "       'fBodyGyro-bandsEnergy()-49,56.2',\n",
       "       'fBodyGyro-bandsEnergy()-57,64.2',\n",
       "       'fBodyGyro-bandsEnergy()-1,16.2',\n",
       "       'fBodyGyro-bandsEnergy()-17,32.2',\n",
       "       'fBodyGyro-bandsEnergy()-33,48.2',\n",
       "       'fBodyGyro-bandsEnergy()-49,64.2',\n",
       "       'fBodyGyro-bandsEnergy()-1,24.2',\n",
       "       'fBodyGyro-bandsEnergy()-25,48.2', 'fBodyAccMag-mean()',\n",
       "       'fBodyAccMag-std()', 'fBodyAccMag-mad()', 'fBodyAccMag-max()',\n",
       "       'fBodyAccMag-min()', 'fBodyAccMag-sma()', 'fBodyAccMag-energy()',\n",
       "       'fBodyAccMag-iqr()', 'fBodyAccMag-entropy()',\n",
       "       'fBodyAccMag-maxInds', 'fBodyAccMag-meanFreq()',\n",
       "       'fBodyAccMag-skewness()', 'fBodyAccMag-kurtosis()',\n",
       "       'fBodyBodyAccJerkMag-mean()', 'fBodyBodyAccJerkMag-std()',\n",
       "       'fBodyBodyAccJerkMag-mad()', 'fBodyBodyAccJerkMag-max()',\n",
       "       'fBodyBodyAccJerkMag-min()', 'fBodyBodyAccJerkMag-sma()',\n",
       "       'fBodyBodyAccJerkMag-energy()', 'fBodyBodyAccJerkMag-iqr()',\n",
       "       'fBodyBodyAccJerkMag-entropy()', 'fBodyBodyAccJerkMag-maxInds',\n",
       "       'fBodyBodyAccJerkMag-meanFreq()', 'fBodyBodyAccJerkMag-skewness()',\n",
       "       'fBodyBodyAccJerkMag-kurtosis()', 'fBodyBodyGyroMag-mean()',\n",
       "       'fBodyBodyGyroMag-std()', 'fBodyBodyGyroMag-mad()',\n",
       "       'fBodyBodyGyroMag-max()', 'fBodyBodyGyroMag-min()',\n",
       "       'fBodyBodyGyroMag-sma()', 'fBodyBodyGyroMag-energy()',\n",
       "       'fBodyBodyGyroMag-iqr()', 'fBodyBodyGyroMag-entropy()',\n",
       "       'fBodyBodyGyroMag-maxInds', 'fBodyBodyGyroMag-meanFreq()',\n",
       "       'fBodyBodyGyroMag-skewness()', 'fBodyBodyGyroMag-kurtosis()',\n",
       "       'fBodyBodyGyroJerkMag-mean()', 'fBodyBodyGyroJerkMag-std()',\n",
       "       'fBodyBodyGyroJerkMag-mad()', 'fBodyBodyGyroJerkMag-max()',\n",
       "       'fBodyBodyGyroJerkMag-min()', 'fBodyBodyGyroJerkMag-sma()',\n",
       "       'fBodyBodyGyroJerkMag-energy()', 'fBodyBodyGyroJerkMag-iqr()',\n",
       "       'fBodyBodyGyroJerkMag-entropy()', 'fBodyBodyGyroJerkMag-maxInds',\n",
       "       'fBodyBodyGyroJerkMag-meanFreq()',\n",
       "       'fBodyBodyGyroJerkMag-skewness()',\n",
       "       'fBodyBodyGyroJerkMag-kurtosis()', 'angle(tBodyAccMean,gravity)',\n",
       "       'angle(tBodyAccJerkMean),gravityMean)',\n",
       "       'angle(tBodyGyroMean,gravityMean)',\n",
       "       'angle(tBodyGyroJerkMean,gravityMean)', 'angle(X,gravityMean)',\n",
       "       'angle(Y,gravityMean)', 'angle(Z,gravityMean)', 'subject',\n",
       "       'Activity', 'Data'], dtype=object)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tt_data.columns.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LAYING                1944\n",
       "STANDING              1906\n",
       "SITTING               1777\n",
       "WALKING               1722\n",
       "WALKING_UPSTAIRS      1544\n",
       "WALKING_DOWNSTAIRS    1406\n",
       "Name: Activity, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tt_data['Activity'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "label = tt_data.pop('Activity')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tBodyAcc-mean()-X</th>\n",
       "      <th>tBodyAcc-mean()-Y</th>\n",
       "      <th>tBodyAcc-mean()-Z</th>\n",
       "      <th>tBodyAcc-std()-X</th>\n",
       "      <th>tBodyAcc-std()-Y</th>\n",
       "      <th>tBodyAcc-std()-Z</th>\n",
       "      <th>tBodyAcc-mad()-X</th>\n",
       "      <th>tBodyAcc-mad()-Y</th>\n",
       "      <th>tBodyAcc-mad()-Z</th>\n",
       "      <th>tBodyAcc-max()-X</th>\n",
       "      <th>...</th>\n",
       "      <th>angle(tBodyAccMean,gravity)</th>\n",
       "      <th>angle(tBodyAccJerkMean),gravityMean)</th>\n",
       "      <th>angle(tBodyGyroMean,gravityMean)</th>\n",
       "      <th>angle(tBodyGyroJerkMean,gravityMean)</th>\n",
       "      <th>angle(X,gravityMean)</th>\n",
       "      <th>angle(Y,gravityMean)</th>\n",
       "      <th>angle(Z,gravityMean)</th>\n",
       "      <th>subject</th>\n",
       "      <th>Activity</th>\n",
       "      <th>Data</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.288585</td>\n",
       "      <td>-0.020294</td>\n",
       "      <td>-0.132905</td>\n",
       "      <td>-0.995279</td>\n",
       "      <td>-0.983111</td>\n",
       "      <td>-0.913526</td>\n",
       "      <td>-0.995112</td>\n",
       "      <td>-0.983185</td>\n",
       "      <td>-0.923527</td>\n",
       "      <td>-0.934724</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.112754</td>\n",
       "      <td>0.030400</td>\n",
       "      <td>-0.464761</td>\n",
       "      <td>-0.018446</td>\n",
       "      <td>-0.841247</td>\n",
       "      <td>0.179941</td>\n",
       "      <td>-0.058627</td>\n",
       "      <td>1</td>\n",
       "      <td>STANDING</td>\n",
       "      <td>Train</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0.278419</td>\n",
       "      <td>-0.016411</td>\n",
       "      <td>-0.123520</td>\n",
       "      <td>-0.998245</td>\n",
       "      <td>-0.975300</td>\n",
       "      <td>-0.960322</td>\n",
       "      <td>-0.998807</td>\n",
       "      <td>-0.974914</td>\n",
       "      <td>-0.957686</td>\n",
       "      <td>-0.943068</td>\n",
       "      <td>...</td>\n",
       "      <td>0.053477</td>\n",
       "      <td>-0.007435</td>\n",
       "      <td>-0.732626</td>\n",
       "      <td>0.703511</td>\n",
       "      <td>-0.844788</td>\n",
       "      <td>0.180289</td>\n",
       "      <td>-0.054317</td>\n",
       "      <td>1</td>\n",
       "      <td>STANDING</td>\n",
       "      <td>Train</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0.279653</td>\n",
       "      <td>-0.019467</td>\n",
       "      <td>-0.113462</td>\n",
       "      <td>-0.995380</td>\n",
       "      <td>-0.967187</td>\n",
       "      <td>-0.978944</td>\n",
       "      <td>-0.996520</td>\n",
       "      <td>-0.963668</td>\n",
       "      <td>-0.977469</td>\n",
       "      <td>-0.938692</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.118559</td>\n",
       "      <td>0.177899</td>\n",
       "      <td>0.100699</td>\n",
       "      <td>0.808529</td>\n",
       "      <td>-0.848933</td>\n",
       "      <td>0.180637</td>\n",
       "      <td>-0.049118</td>\n",
       "      <td>1</td>\n",
       "      <td>STANDING</td>\n",
       "      <td>Train</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0.279174</td>\n",
       "      <td>-0.026201</td>\n",
       "      <td>-0.123283</td>\n",
       "      <td>-0.996091</td>\n",
       "      <td>-0.983403</td>\n",
       "      <td>-0.990675</td>\n",
       "      <td>-0.997099</td>\n",
       "      <td>-0.982750</td>\n",
       "      <td>-0.989302</td>\n",
       "      <td>-0.938692</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.036788</td>\n",
       "      <td>-0.012892</td>\n",
       "      <td>0.640011</td>\n",
       "      <td>-0.485366</td>\n",
       "      <td>-0.848649</td>\n",
       "      <td>0.181935</td>\n",
       "      <td>-0.047663</td>\n",
       "      <td>1</td>\n",
       "      <td>STANDING</td>\n",
       "      <td>Train</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0.276629</td>\n",
       "      <td>-0.016570</td>\n",
       "      <td>-0.115362</td>\n",
       "      <td>-0.998139</td>\n",
       "      <td>-0.980817</td>\n",
       "      <td>-0.990482</td>\n",
       "      <td>-0.998321</td>\n",
       "      <td>-0.979672</td>\n",
       "      <td>-0.990441</td>\n",
       "      <td>-0.942469</td>\n",
       "      <td>...</td>\n",
       "      <td>0.123320</td>\n",
       "      <td>0.122542</td>\n",
       "      <td>0.693578</td>\n",
       "      <td>-0.615971</td>\n",
       "      <td>-0.847865</td>\n",
       "      <td>0.185151</td>\n",
       "      <td>-0.043892</td>\n",
       "      <td>1</td>\n",
       "      <td>STANDING</td>\n",
       "      <td>Train</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 564 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   tBodyAcc-mean()-X  tBodyAcc-mean()-Y  tBodyAcc-mean()-Z  tBodyAcc-std()-X  \\\n",
       "0           0.288585          -0.020294          -0.132905         -0.995279   \n",
       "1           0.278419          -0.016411          -0.123520         -0.998245   \n",
       "2           0.279653          -0.019467          -0.113462         -0.995380   \n",
       "3           0.279174          -0.026201          -0.123283         -0.996091   \n",
       "4           0.276629          -0.016570          -0.115362         -0.998139   \n",
       "\n",
       "   tBodyAcc-std()-Y  tBodyAcc-std()-Z  tBodyAcc-mad()-X  tBodyAcc-mad()-Y  \\\n",
       "0         -0.983111         -0.913526         -0.995112         -0.983185   \n",
       "1         -0.975300         -0.960322         -0.998807         -0.974914   \n",
       "2         -0.967187         -0.978944         -0.996520         -0.963668   \n",
       "3         -0.983403         -0.990675         -0.997099         -0.982750   \n",
       "4         -0.980817         -0.990482         -0.998321         -0.979672   \n",
       "\n",
       "   tBodyAcc-mad()-Z  tBodyAcc-max()-X  ...  angle(tBodyAccMean,gravity)  \\\n",
       "0         -0.923527         -0.934724  ...                    -0.112754   \n",
       "1         -0.957686         -0.943068  ...                     0.053477   \n",
       "2         -0.977469         -0.938692  ...                    -0.118559   \n",
       "3         -0.989302         -0.938692  ...                    -0.036788   \n",
       "4         -0.990441         -0.942469  ...                     0.123320   \n",
       "\n",
       "   angle(tBodyAccJerkMean),gravityMean)  angle(tBodyGyroMean,gravityMean)  \\\n",
       "0                              0.030400                         -0.464761   \n",
       "1                             -0.007435                         -0.732626   \n",
       "2                              0.177899                          0.100699   \n",
       "3                             -0.012892                          0.640011   \n",
       "4                              0.122542                          0.693578   \n",
       "\n",
       "   angle(tBodyGyroJerkMean,gravityMean)  angle(X,gravityMean)  \\\n",
       "0                             -0.018446             -0.841247   \n",
       "1                              0.703511             -0.844788   \n",
       "2                              0.808529             -0.848933   \n",
       "3                             -0.485366             -0.848649   \n",
       "4                             -0.615971             -0.847865   \n",
       "\n",
       "   angle(Y,gravityMean)  angle(Z,gravityMean)  subject  Activity   Data  \n",
       "0              0.179941             -0.058627        1  STANDING  Train  \n",
       "1              0.180289             -0.054317        1  STANDING  Train  \n",
       "2              0.180637             -0.049118        1  STANDING  Train  \n",
       "3              0.181935             -0.047663        1  STANDING  Train  \n",
       "4              0.185151             -0.043892        1  STANDING  Train  \n",
       "\n",
       "[5 rows x 564 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>fBodyAcc</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>fBodyGyro</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>fBodyAccJerk</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>tGravityAcc</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>tBodyAcc</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>tBodyGyroJerk</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>tBodyGyro</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>tBodyAccJerk</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>tBodyAccMag</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>tGravityAccMag</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>tBodyAccJerkMag</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>tBodyGyroMag</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>tBodyGyroJerkMag</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>fBodyAccMag</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>fBodyBodyAccJerkMag</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>fBodyBodyGyroMag</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>fBodyBodyGyroJerkMag</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>angle</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>subject</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Data</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      count\n",
       "fBodyAcc                 79\n",
       "fBodyGyro                79\n",
       "fBodyAccJerk             79\n",
       "tGravityAcc              40\n",
       "tBodyAcc                 40\n",
       "tBodyGyroJerk            40\n",
       "tBodyGyro                40\n",
       "tBodyAccJerk             40\n",
       "tBodyAccMag              13\n",
       "tGravityAccMag           13\n",
       "tBodyAccJerkMag          13\n",
       "tBodyGyroMag             13\n",
       "tBodyGyroJerkMag         13\n",
       "fBodyAccMag              13\n",
       "fBodyBodyAccJerkMag      13\n",
       "fBodyBodyGyroMag         13\n",
       "fBodyBodyGyroJerkMag     13\n",
       "angle                     7\n",
       "subject                   1\n",
       "Data                      1"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame.from_dict(Counter([col.split('-')[0].split('(')[0] for col in tt_data.columns]),\n",
    "orient = 'index').rename(columns = {0:'count'}).sort_values('count',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Null values in DataFrame:0\n",
      "\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 10299 entries, 0 to 10298\n",
      "Columns: 563 entries, tBodyAcc-mean()-X to Data\n",
      "dtypes: float64(561), object(2)\n",
      "memory usage: 44.2+ MB\n"
     ]
    }
   ],
   "source": [
    "print('Null values in DataFrame:{}\\n'.format(tt_data.isna().sum().sum()))\n",
    "tt_data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "linkText": "Export to plot.ly",
        "plotlyServerURL": "https://plot.ly",
        "showLink": false
       },
       "data": [
        {
         "marker": {
          "color": [
           "#440154",
           "#414487",
           "#2a788e",
           "#22a884",
           "#7ad151",
           "#fde725"
          ]
         },
         "type": "bar",
         "x": [
          "LAYING",
          "STANDING",
          "SITTING",
          "WALKING",
          "WALKING_UPSTAIRS",
          "WALKING_DOWNSTAIRS"
         ],
         "y": [
          1944,
          1906,
          1777,
          1722,
          1544,
          1406
         ]
        }
       ],
       "layout": {
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "title": {
         "text": "Smartphone Activity Label Distribution"
        },
        "xaxis": {
         "title": {
          "text": "Activity"
         }
        },
        "yaxis": {
         "title": {
          "text": "Count"
         }
        }
       }
      },
      "text/html": [
       "<div>\n",
       "        \n",
       "        \n",
       "            <div id=\"c035030b-58b2-43b1-ae6d-309b7865a8f0\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
       "            <script type=\"text/javascript\">\n",
       "                require([\"plotly\"], function(Plotly) {\n",
       "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
       "                    \n",
       "                if (document.getElementById(\"c035030b-58b2-43b1-ae6d-309b7865a8f0\")) {\n",
       "                    Plotly.newPlot(\n",
       "                        'c035030b-58b2-43b1-ae6d-309b7865a8f0',\n",
       "                        [{\"marker\": {\"color\": [\"#440154\", \"#414487\", \"#2a788e\", \"#22a884\", \"#7ad151\", \"#fde725\"]}, \"type\": \"bar\", \"x\": [\"LAYING\", \"STANDING\", \"SITTING\", \"WALKING\", \"WALKING_UPSTAIRS\", \"WALKING_DOWNSTAIRS\"], \"y\": [1944, 1906, 1777, 1722, 1544, 1406]}],\n",
       "                        {\"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"text\": \"Smartphone Activity Label Distribution\"}, \"xaxis\": {\"title\": {\"text\": \"Activity\"}}, \"yaxis\": {\"title\": {\"text\": \"Count\"}}},\n",
       "                        {\"responsive\": true}\n",
       "                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('c035030b-58b2-43b1-ae6d-309b7865a8f0');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })\n",
       "                };\n",
       "                });\n",
       "            </script>\n",
       "        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "label_counts = label.value_counts()\n",
    "\n",
    "n = label_counts.shape[0]\n",
    "colormap = get_cmap('viridis')\n",
    "colors = [rgb2hex(colormap(col)) for col in np.arange(0,1.01,1/(n-1))]\n",
    "\n",
    "data = go.Bar(x = label_counts.index,\n",
    "             y = label_counts,\n",
    "             marker = dict(color = colors))\n",
    "\n",
    "layout = go.Layout(title = 'Smartphone Activity Label Distribution',\n",
    "                  xaxis = dict(title = 'Activity'),\n",
    "                  yaxis = dict(title = 'Count'))\n",
    "\n",
    "fig = go.Figure(data = [data], layout=layout)\n",
    "iplot(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tsne_data = tt_data.copy()\n",
    "data_data = tsne_data.pop('Data')\n",
    "subject_data = tsne_data.pop('subject')\n",
    "\n",
    "# Scale data\n",
    "scl = StandardScaler()\n",
    "tsne_data = scl.fit_transform(tsne_data)\n",
    "\n",
    "# Reduce dimensions (speed up)\n",
    "pca = PCA(n_components=0.9, random_state=3)\n",
    "tsne_data = pca.fit_transform(tsne_data)\n",
    "\n",
    "# Transform data\n",
    "tsne = TSNE(random_state=3)\n",
    "tsne_transformed = tsne.fit_transform(tsne_data)\n",
    "\n",
    "\n",
    "# Create subplots\n",
    "fig, axarr = plt.subplots(2, 1, figsize=(15,10))\n",
    "\n",
    "### Plot Activities\n",
    "# Get colors\n",
    "n = label.unique().shape[0]\n",
    "colormap = get_cmap('viridis')\n",
    "colors = [rgb2hex(colormap(col)) for col in np.arange(0, 1.01, 1/(n-1))]\n",
    "\n",
    "# Plot each activity\n",
    "for i, group in enumerate(label_counts.index):\n",
    "    # Mask to separate sets\n",
    "    mask = (label==group).values\n",
    "    axarr[0].scatter(x=tsne_transformed[mask][:,0], y=tsne_transformed[mask][:,1], c=colors[i], alpha=0.5, label=group)\n",
    "axarr[0].set_title('TSNE: Activity Visualisation')\n",
    "axarr[0].legend()\n",
    "\n",
    "\n",
    "### Plot Subjects\n",
    "# Get colors\n",
    "n = subject_data.unique().shape[0]\n",
    "colormap = get_cmap('gist_ncar')\n",
    "colors = [rgb2hex(colormap(col)) for col in np.arange(0, 1.01, 1/(n-1))]\n",
    "\n",
    "# Plot each participant\n",
    "for i, group in enumerate(subject_data.unique()):\n",
    "    # Mask to separate sets\n",
    "    mask = (subject_data==group).values\n",
    "    axarr[1].scatter(x=tsne_transformed[mask][:,0], y=tsne_transformed[mask][:,1], c=colors[i], alpha=0.5, label=group)\n",
    "\n",
    "axarr[1].set_title('TSNE: Participant Visualisation')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1008x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create dataset\n",
    "tsne_data = tt_data[label=='WALKING'].copy()\n",
    "data_data = tsne_data.pop('Data')\n",
    "subject_data = tsne_data.pop('subject')\n",
    "\n",
    "# Scale data\n",
    "scl = StandardScaler()\n",
    "tsne_data = scl.fit_transform(tsne_data)\n",
    "\n",
    "# Split training testing data\n",
    "enc = LabelEncoder()\n",
    "label_encoded = enc.fit_transform(subject_data)\n",
    "X_train, X_test, y_train, y_test = train_test_split(tsne_data, label_encoded, random_state=3)\n",
    "\n",
    "\n",
    "# Create model\n",
    "lgbm = LGBMClassifier(n_estimators=500, random_state=3)\n",
    "lgbm = lgbm.fit(X_train, y_train)\n",
    "\n",
    "# Get importances\n",
    "features = tt_data.drop(['Data', 'subject'], axis=1).columns\n",
    "importances = lgbm.feature_importances_\n",
    "\n",
    "# Sum importances\n",
    "data = {'Gyroscope':0, 'Accelerometer':0}\n",
    "for importance, feature in zip(importances, features):\n",
    "    if 'Gyro' in feature:\n",
    "        data['Gyroscope'] += importance\n",
    "    if 'Acc' in feature:\n",
    "        data['Accelerometer'] += importance\n",
    "        \n",
    "# Create dataframe and plot\n",
    "sensor_df = pd.DataFrame.from_dict(data, orient='index').rename(columns={0:'Importance'})\n",
    "sensor_df.plot(kind='barh', figsize=(14,4), title='Sensor Importance For Classifing Participants By Walking Style (Feature Importance Sum)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_data = pd.read_csv('/home/siddharth/Desktop/train.csv')\n",
    "test_data = pd.read_csv('/home/siddharth/Desktop/test.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#subject col is not useful hence dropped\n",
    "if('subject' in train_data.columns):\n",
    "    train_data.drop('subject', axis=1, inplace=True)\n",
    "if('subject' in test_data.columns):\n",
    "    test_data.drop('subject', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Encoding target - converting non-numto num variable\n",
    "le = preprocessing.LabelEncoder()\n",
    "for x in [train_data,  test_data]:\n",
    "    x['Activity'] = le.fit_transform(x.Activity)\n",
    "\n",
    "# Split into features and class\n",
    "df_traindata, df_trainlabel = train_data.iloc[:,0:len(train_data.columns)-1],train_data.iloc[:,-1]\n",
    "df_testdata, df_testlabel = test_data.iloc[:,0:len(test_data.columns)-1],test_data.iloc[:,-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1407\n",
       "2    1374\n",
       "1    1286\n",
       "3    1226\n",
       "5    1073\n",
       "4     986\n",
       "Name: Activity, dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_trainlabel.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 360x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Baseline Comparing model accuracy using all features accross classifiers\n",
    "classifiers = [\n",
    "    DecisionTreeClassifier(),\n",
    "    RandomForestClassifier(),\n",
    "    KNeighborsClassifier(),\n",
    "    SVC(kernel=\"linear\"),\n",
    "    GaussianNB(),\n",
    "    LogisticRegression()\n",
    "    ]\n",
    "\n",
    "\n",
    "# Naive Train Accuracy\n",
    "algo = []\n",
    "scores = []\n",
    "for clf in classifiers:\n",
    "    algo.append(clf.__class__.__name__)\n",
    "    scores.append(cross_val_score(clf,df_traindata,df_trainlabel, cv=5).mean())\n",
    "warnings.filterwarnings('ignore')\n",
    "Naivescore_df_Train = pd.DataFrame({'Algorithm': algo, 'Score': scores}).set_index('Algorithm')\n",
    "\n",
    "\n",
    "# Naive Test Accuracy\n",
    "\n",
    "algo = []\n",
    "scores = []\n",
    "\n",
    "for clf in classifiers:\n",
    "    clf = clf.fit(df_traindata, df_trainlabel)\n",
    "    y_pred = clf.predict(df_testdata)\n",
    "    algo.append(clf.__class__.__name__)\n",
    "    scores.append(accuracy_score(y_pred, df_testlabel))\n",
    "warnings.filterwarnings('ignore')\n",
    "Naivescore_df_Test  = pd.DataFrame({'Algorithm': algo, 'Score': scores}).set_index('Algorithm')\n",
    "\n",
    "# Bar plot between Train and Test Accuracy\n",
    "fig = plt.figure(figsize=(5,5)) \n",
    "\n",
    "ax = fig.add_subplot(111) \n",
    "ax2 = ax.twinx() \n",
    "width = .3\n",
    "\n",
    "Naivescore_df_Train.Score.plot(kind='bar',color='green',ax=ax,width=width, position=0)\n",
    "Naivescore_df_Test.Score.plot(kind='bar',color='red', ax=ax2,width = width,position=1)\n",
    "\n",
    "ax.set_ylabel('Train')\n",
    "ax2.set_ylabel('Test')\n",
    "\n",
    "ax.set_xlim(-1,7)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1008x936 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Feature selection using Random Forest Classifer\n",
    "# Bagged decision trees for feature importance - embedded method\n",
    "Rtree_clf_1 = RandomForestClassifier()\n",
    "Rtree_clf = Rtree_clf_1.fit(df_traindata, df_trainlabel)\n",
    "model = SelectFromModel(Rtree_clf,prefit = True)\n",
    "RF_tree_featuresTrain = df_traindata.loc[:,model.get_support()]\n",
    "RF_tree_featuresTest = df_testdata.loc[:,model.get_support()]\n",
    "\n",
    "# Feature Importance\n",
    "\n",
    "importances = Rtree_clf.feature_importances_\n",
    "std = np.std([tree.feature_importances_ for tree in Rtree_clf.estimators_],axis=0)\n",
    "indices = np.argsort(importances)[::-1]\n",
    "indices.shape\n",
    "indices = indices[:200]\n",
    "\n",
    "#Plot feature importances\n",
    "\n",
    "plt.figure(1, figsize=(14,13))\n",
    "plt.title('Feature importances')\n",
    "plt.xlabel('# of features')\n",
    "plt.ylabel('Importance score')\n",
    "plt.bar(range(200), importances[indices],color='r',yerr=std[indices],align='center')\n",
    "plt.xlim([0,200])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f86e4361510>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZMAAAEWCAYAAACjYXoKAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAgAElEQVR4nOzdeZgU1bn48e/by+zDsA/7YgSVVXFEMC7jRkiEqJhcNSQuP5VrEoy7YDRquBJJ4nVJXBK8bjFciVeDW1AE4uAGCiiogAiSCMOMyjrMPr28vz+qu+mZ6Vm7m1l4P8/TT1edOnX6VDH023XqnFOiqhhjjDHxcLV1BYwxxnR8FkyMMcbEzYKJMcaYuFkwMcYYEzcLJsYYY+JmwcQYY0zcLJgYk2Ai8pqIXNrW9TDmULJgYjoNEfm3iJzV1vVQ1e+q6tPJKFtEuojIAyKyXUTKRGRraL1nMj7PmOayYGJMC4iIpw0/OwVYDowEJgNdgJOAPcD4VpTXZsdiOh8LJuawICJTRGSdiOwXkfdEZEzUttki8oWIlIrIRhE5P2rbZSLyrojcLyJ7gbtCae+IyL0isk9E/iUi343ap0BErozav7G8Q0XkrdBnLxORh0Xkrw0cxiXAIOB8Vd2oqkFV/UZV/0tVF4fKUxE5Mqr8p0Tk7tByvogUisgsEfkKeFJENonIlKj8HhHZLSLjQusTQudrv4isF5H8eP4dTOdlwcR0eqEvxieA/wR6AH8GXhaR1FCWL4BTgBzg18BfRaRvVBEnAtuA3sDcqLTNQE/gd8DjIiINVKGxvP8LfBCq113ATxo5lLOA11W1rOmjblAfoDswGJgBPAtcHLX9O8BuVf1QRPoD/wDuDu1zE/CCiPSK4/NNJ2XBxBwOrgL+rKrvq2ogdD+jGpgAoKr/p6pFoV/6fwO2ULvZqEhV/6iqflWtDKV9qaqPqWoAeBroC+Q28Pkx84rIIOAE4A5VrVHVd4CXGzmOHkBxq87AQUHgTlWtDh3L/wLfF5GM0PYfhdIAfgwsVtXFoXOzFFgDfC/OOphOyIKJORwMBm4MNdXsF5H9wECgH4CIXBLVBLYfGIVzFRG2I0aZX4UXVLUitJjVwOc3lLcfsDcqraHPCtuDE4jisUtVq6LqsxXYBEwNBZTvczCYDAZ+WOe8nZyAOphOyG7AmcPBDmCuqs6tu0FEBgOPAWcCK1U1ICLrgOgmq2RNrV0MdBeRjKiAMrCR/MuAu0UkU1XLG8hTAWRErfcBCqPWYx1LuKnLBWwMBRhwztszqnpVE8dhjF2ZmE7HKyJpUS8PTrC4WkROFEemiJwjItlAJs4X7C4AEbkc58ok6VT1S5xmo7tEJEVEJgJTG9nlGZwv+BdE5GgRcYlIDxH5pYiEm57WAT8SEbeITAZOa0ZVFgKTgJ9y8KoE4K84VyzfCZWXFrqJP6CFh2oOAxZMTGezGKiMet2lqmtw7ps8BOwDtgKXAajqRuC/gZXA18Bo4N1DWN/pwEScJqy7gb/h3M+pR1WrcW7CfwYsBQ7g3LzvCbwfynYtTkDaHyr7xaYqoKrFOMd/Uujzw+k7gHOBX+IE2x3Azdj3holB7OFYxrQfIvI34DNVvbOt62JMS9gvDGPakIicICLfCjVZTca5EmjyasKY9sZuwBvTtvoAf8fp9lsI/FRVP2rbKhnTctbMZYwxJm7WzGWMMSZuh0UzV8+ePXXIkCFtXY24lZeXk5mZ2dbVaFfsnNRn56Q+Oyf1NeecrF27dreqNmv6nMMimAwZMoQ1a9a0dTXiVlBQQH5+fltXo12xc1KfnZP67JzU15xzIiJfNrc8a+YyxhgTNwsmxhhj4mbBxBhjTNwsmBhjjImbBRNjjDFxS2owEZEnROQbEfm0ge0iIn8Qka0i8nH4UaGhbZeKyJbQ69Ko9ONF5JPQPn9o5Ol28VmwAIYMAZfLeV+wICkfY4wxnUGyr0yeAiY3sv27wLDQawbwKICIdAfuxHnc6XjgThHpFtrn0VDe8H6Nld86CxbAjBnw5Zeg6rzPmGEBpTEWfFvGzlfL2PlqmTY4X0kdZ6Kqb4nIkEaynAv8RZ05XVaJSNfQs7fzgaWquhdARJYCk0WkAOiiqitD6X8BzgNeS2jFb7sNKipqp1VUwLXXOsHF7Xb+kcKv6PXmbmtFGd79+2Hv3sb3E3Feh1I4+IbPWTj4AkyffmjrkmiqzisYrL8cK62p7cEgLFoEs2dDZegJwF9+CVddBbt2wfnn1/43bMlyaN1TUuL8nTSRr7nlNWs5mTrz31cytNH5SvrcXKFg8qqq1nvgkIi8CswLPfsaEVkOzMIJJmmqenco/Vc4z6YoCOU/K5R+CjBLVafEKHsGzhUMubm5xy9cuLDZdT7tjDOQDjxnmYqgoQCjIs67ywWh9Ohl6uTVUECKua2BMrM3bcLt89WrR8Dr5cDIkaDqnM/QK7wswWCowlHbg0HnEYfRy6F8Ev4yBmdfVTQYdC6vo8uI2l5ruYF6NFi/Dvw30Ba0TnDRBoKO1g1IDeyPCCqCp7w85r+FiuDr0qVeOdH7hwUBaSj4xapzA9vDy4nO12TeFtQxY/t2XH5/vSxVubmsivoeLCsrIyuroSdNO04//fS1qprXaKaQth4BH+tnjbYivX6i6nxgPkBeXp62aPTroEFONK+rb1947TXnCy0QcL58/H5nPRg8uFz3PXo5EDj4Cn/J1d3WQPlbvvqKYT16xP7sqJcEAs4XaEOv8P6N5WnuSxViBBIAt89Ht1DgIfodnGWonV43LZwv+pdydH4Rvqqqok9GRu18sfZtopxmpzV3e/SxuN216/OrXzX8tzd3biQIEhUcay1Hr8dI37JnD8O6d4+9f0PlRQX2eu/NWYaDX/jhgN/cY2igvEja/0Y//PEgUSVl8uT6+9WlSlF5Of0yMmqlNbhP3To2tk9j+ze1bzz7NFbHbdtifkTaN9/UGvGe6FkB2jqYFFL7mdcDgKJQen6d9IJQ+oAY+RNr7tzal4kAGRnw+9/D2LEJ/7jm2llQwLBY//jN/YNPxrZgEEaPhh076tdrwABYvvzgF2u0WGlN/YqLkfbZqlX0mTgxIWU1mh5PeXXTHnsMtm+vn2/wYPjlLxv+wqmrgXw733qLYaee2mie5pbVZnmi8739duy/r4ED4amnmlXU5ytX0i/W30lnNHx47PM1aFBSP7atg8nLwEwRWYhzs71EVYtFZAnwm6ib7pOAW1V1r4iUisgEnMeUXgL8MeG1Crcr3nab859+0CAnwLTX9tkGLpsPmXvuiR18582Dbt0a3i8RXC5IT0/uZyTab34T+3zNnessN/ffsLF8sYJ1R9XQ39c990BaWvPKEGl+3o6uofMV/vtKkqQGExF5FucKo6eIFOL00PICqOqfcJ7X/T2cZ3JXAJeHtu0Vkf8CVoeKmhO+GQ/8FKeXWDrOjffE3nwPmz69/QaP9qajBd+2ZuerZex8tUwbna9k9+a6uIntCvy8gW1PAE/ESF8D1LuZb9qYBd+WsfPVMna+WqYNzlcnuhY2xhjTViyYGGOMiZsFE2OMMXGzYGKMMSZuFkyMMcbEzYKJMcaYuFkwMcYYEzcLJsYYY+JmwcQYY0zcLJgYY4yJmwUTY4wxcbNgYowxJm4WTIwxxsTNgokxxpi4WTAxxhgTNwsmxhhj4mbBxBhjTNwsmBhjjIlbUoOJiEwWkc0islVEZsfYPlhElovIxyJSICIDQumni8i6qFeViJwX2vaUiPwratuxyTwGY4wxTUvaM+BFxA08DJwNFAKrReRlVd0Yle1e4C+q+rSInAHcA/xEVd8Ejg2V0x3YCrwRtd/Nqvp8supujDGmZZJ5ZTIe2Kqq21S1BlgInFsnzwhgeWj5zRjbAX4AvKaqFUmrqTHGmLgk7coE6A/siFovBE6sk2c9cAHwIHA+kC0iPVR1T1Sei4D76uw3V0TuwAlEs1W1uu6Hi8gMYAZAbm4uBQUFcRxK+1BWVtYpjiOR7JzUZ+ekPjsn9SX6nCQzmEiMNK2zfhPwkIhcBrwF7AT8kQJE+gKjgSVR+9wKfAWkAPOBWcCceh+kOj+0nby8PM3Pz2/lYbQfBQUFdIbjSCQ7J/XZOanPzkl9iT4nyQwmhcDAqPUBQFF0BlUtAqYBiEgWcIGqlkRl+Q9gkar6ovYpDi1Wi8iTOAHJGGNMG0rmPZPVwDARGSoiKTjNVS9HZxCRniISrsOtwBN1yrgYeLbOPn1D7wKcB3yahLobY4xpgaQFE1X1AzNxmqg2Ac+p6gYRmSMi3w9lywc2i8jnQC4wN7y/iAzBubJZUafoBSLyCfAJ0BO4O1nHYIwxpnmS2cyFqi4GFtdJuyNq+XkgZhdfVf03zk38uulnJLaWxhhj4mUj4I0xxsTNgokxxpi4WTAxxhgTNwsmxhhj4mbBxBhjTNwsmBhjjImbBRNjjDFxs2BijDEmbhZMjDHGxM2CiTHGmLhZMDHGGBM3CybGGGPiZsHEGGNM3CyYGGOMiZsFE2OMMXGzYGKMMSZuFkyMMcbEzYKJMcaYuCU1mIjIZBHZLCJbRWR2jO2DRWS5iHwsIgUiMiBqW0BE1oVeL0elDxWR90Vki4j8TURSknkMxhhjmpa0YCIibuBh4LvACOBiERlRJ9u9wF9UdQwwB7gnalulqh4ben0/Kv23wP2qOgzYB1yRrGMwxhjTPMm8MhkPbFXVbapaAywEzq2TZwSwPLT8ZozttYiIAGcAz4eSngbOS1iNjTHGtIoniWX3B3ZErRcCJ9bJsx64AHgQOB/IFpEeqroHSBORNYAfmKeqLwI9gP2q6o8qs3+sDxeRGcAMgNzcXAoKChJyUG2prKysUxxHItk5qc/OSX12TupL9DlJZjCRGGlaZ/0m4CERuQx4C9iJEzwABqlqkYgcAfxTRD4BDjSjTCdRdT4wHyAvL0/z8/NbfADtTUFBAZ3hOBLJzkl9dk7qs3NSX6LPSTKDSSEwMGp9AFAUnUFVi4BpACKSBVygqiVR21DVbSJSABwHvAB0FRFP6OqkXpnGGGMOvWTeM1kNDAv1vkoBLgJejs4gIj1FJFyHW4EnQundRCQ1nAf4NrBRVRXn3soPQvtcCryUxGMwxhjTDEkLJqErh5nAEmAT8JyqbhCROSIS7p2VD2wWkc+BXGBuKP0YYI2IrMcJHvNUdWNo2yzgBhHZinMP5fFkHYMxxpjmSWYzF6q6GFhcJ+2OqOXnOdgzKzrPe8DoBsrchtNTzBhjTDthI+CNMcbEzYKJMcaYuFkwMcYYEzcLJsYYY+JmwcQYY0zcLJgYY4yJmwUTY4wxcbNgYowxJm4WTIwxxsTNgokxxpi4WTAxxhgTNwsmxhhj4mbBxBhjTNwsmBhjjImbBRNjjDFxs2BijDEmbhZMjDHGxM2CiTHGmLglNZiIyGQR2SwiW0Vkdoztg0VkuYh8LCIFIjIglH6siKwUkQ2hbRdG7fOUiPxLRNaFXscm8xiMMcY0LWnBRETcwMPAd4ERwMUiMqJOtnuBv6jqGGAOcE8ovQK4RFVHApOBB0Ska9R+N6vqsaHXumQdgzHGmOZJ5pXJeGCrqm5T1RpgIXBunTwjgOWh5TfD21X1c1XdElouAr4BeiWxrsYYY+KQzGDSH9gRtV4YSou2HrggtHw+kC0iPaIziMh4IAX4Iip5bqj5634RSU1stY0xxrSUqGpyChb5IfAdVb0ytP4TYLyqXhOVpx/wEDAUeAsnsIxU1ZLQ9r5AAXCpqq6KSvsKJ8DMB75Q1TkxPn8GMAMgNzf3+IULFyblOA+lsrIysrKy2roa7Yqdk/rsnNRn56S+5pyT008/fa2q5jWnPE9CahVbITAwan0AUBSdIdSENQ1ARLKAC6ICSRfgH8Dt4UAS2qc4tFgtIk8CN8X6cFWdjxNsyMvL0/z8/AQcUtsqKCigMxxHItk5qc/OSX12TupL9DlJZjPXamCYiAwVkRTgIuDl6Awi0lNEwnW4FXgilJ4CLMK5Of9/dfbpG3oX4Dzg0yQegzHGmGZIWjBRVT8wE1gCbAKeU9UNIjJHRL4fypYPbBaRz4FcYG4o/T+AU4HLYnQBXiAinwCfAD2Bu5N1DMYYY5onmc1cqOpiYHGdtDuilp8Hno+x31+BvzZQ5hkJrqYxxpg42Qh4Y4wxcWt2MBGRk0Xk8tByLxEZmrxqGWOM6UiaFUxE5E5gFs5NcgAvDTRDGWOMOfw098rkfOD7QDlEuvRmJ6tSxhhjOpbmBpMadUY3KoCIZCavSsYYYzqa5gaT50Tkz0BXEbkKWAY8lrxqGWOM6Uia1TVYVe8VkbOBA8BRwB2qujSpNTPGGNNhNBlMQlPJL1HVswALIMYYY+ppsplLVQNAhYjkHIL6GGOM6YCaOwK+CvhERJYS6tEFoKq/SEqtjDHGdCjNDSb/CL2MMcaYepp7A/7p0Ey+w0NJm1XVl7xqGWOMiUcgGKDKX0WqJxWPK6nTMALNDCYikg88DfwbEGCgiFyqqm8lr2rGGGNawh/0U+WvYn/lfip8FfiCPoZ0HYInpZ0EE+C/gUmquhlARIYDzwLHJ6tixhhjmuYL+Kj0VbK/ej9V/ioAvC4vWalZlNWUHbJ6NDeYeMOBBEBVPxcRb5LqZIwxphE1gRoqfZXsq9xHTaAGgBRPClkpbfdo4uYGkzUi8jjwTGh9OrA2OVUyxhgTTVWpCdRQ4atgX9U+/EE/gpDiTiErtX082765weSnwM+BX+DcM3kLeCRZlTLGmMOdqlIdqKasuowD1QfwBX24xEWqJ5U0T1pbV6+e5gYTD/Cgqt4HkVHxqUmrlTHGHIaCGqTaX01pTSkHqg8QCAZwu9ykulNJ87a/ABKtuRM9LgfSo9bTcSZ7bJSITBaRzSKyVURmx9g+WESWi8jHIlIgIgOitl0qIltCr0uj0o8XkU9CZf5BRKSZx2CMMe1OUINU+Cr4qvQrvtj7BdtLtlNaXUqaJ43s1GwyvBm4Xe62rmaTmntlkqaqkW4BqlomIhmN7RC6enkYOBsoBFaLyMuqujEq273AX0LjWM4A7gF+IiLdgTuBPJxp79eG9t0HPArMAFbhPF9+MvBaM4/DGGPaXHgMSEl1CeU15QQ1iMflIcObQUf9fdzcYFIuIuNU9UMAEckDKpvYZzywVVW3hfZZCJwLRAeTEcD1oeU3gRdDy98Blqrq3tC+S4HJIlIAdFHVlaH0vwDnYcHEGNPO1R0DAuBxd+wAEq25weQ64P9EpAjnSqEfcGET+/QHdkStFwIn1smzHrgAeBDnaY7ZItKjgX37h16FMdKNMabdaWwMSGfTaDARkROAHaq6WkSOBv4TmAa8DvyribJjhVqts34T8JCIXIbTQ2wn4G9k3+aUGa77DJzmMHJzcykoKGiiuu1fWVlZpziORLJzUp+dk/oO5TlRlKAGCQQDOA+oBRFpk6uPoAYpdBXikvq3xxN9Tpq6MvkzcFZoeSLwS+Aa4FhgPvCDRvYtBAZGrQ8AiqIzhJ4lPw1ARLKAC1S1REQKgfw6+xaEyhxQJ71WmVFlzw/Vkby8PM3Pz4+VrUMpKCigMxxHItk5qc/OSX3JPCfhMSDlvnL2V+3HFzjYhfdQzInVmLKaMvpn9yczpf6T1hN9Tpo6Unf4vgVOs9Z8VX0BeEFE1jWx72pgmIgMxbniuAj4UXQGEekJ7FXVIHAr8ERo0xLgNyLSLbQ+CbhVVfeKSKmITADeBy4B/tjkURpjTAJ1tDEgh0KTwUREPKrqB84k1GzUnH1V1S8iM3ECgxt4QlU3iMgcYI2qvoxz9XGPiChOM9fPQ/vuFZH/wglIAHOigtpPgadwuie/ht18N8YcAh15DMih0FQweRZYISK7cXpvvQ0gIkcCJU0VrqqLcbrvRqfdEbX8PPB8A/s+wcErlej0NcCopj7bGGPiFdQgVf4qDlQdoLSmNNKFN82TFvM+xOGsqauLuSKyHOgLvKHhu0nOYMdrkl05Y4w51DrjGJBDocm7Q6q6Kkba58mpjjHGHHr+oJ9KXyUlVSVU+CpQFK/bawGkBdq2q4ExxrQRX8BHha+CkuoSKn2ViEinHQNyKFgwMQmjqpT7ylFVXOJCRJx3nPfoNGPaQk2ghvKackqqSqgOVDvTuHtSyE7NbuuqdXgWTExC+IN+vi77mtLqUlyuULDQ8JsebCoIpblcLtzixuPy4BIXHpcHt7hxu5y0xgKR0DYDwEzHEx4DEtAA2/ZtqzUGJNvTeQPI3zf9nXnvzKOotIgBXQZwz1n3MH309KR+pgUTE7dKXyU7D+xEROiS1qVZ+wQ1iGpopLAGqA5Uo6qR0cONBSJFcbvcuMVNTaCGnQd2RgJSODi5Xe4GA1F43XROscaA+IN+vC7vYTEG5O+b/s4tS2+h0u9Mn7jjwA5mvOKM6khmQLFgYlpNVdlXtY9vyr4h3ZuO1938Jzm7xAUCblo3tXY4EAH4gr5IcFLUeQ8t1w1EAIjz+S6coFM3EIXf6wYiC0btV1NjQMI/MA4H896ZFwkkYRW+Cm5bfpsFE9P++IN+ikuLqfBVkJ2afci/XEUEt7gRcR5d2lLRV0EBDeD3+yPBKRyYIjPBNXCVFH0VFKu5zu4bJZeNAamv8EAhO0t3xty2vWR7Uj/bgolpsQpfBUUHihCRDnvjUkQiX/CtER2Mwl9q4auioAbRgxEo6kOplRa+b1S3DuG6Hdyt/j2iuvtEr/uDfr4p/yauMhpKq1tG9Gc0N0+8ZVQHqjlQfcDGgITsPLCTV7e8yiubX+Gjrz5qMN+gnEFJrYcFE9Ns8TRrdTbxBiOgVtNctLppitYKSgfHDlM7T1S5pdWljX523c+MVW6setX74q+zWjdPrau5g4ktKqNuHlUbA7KzdCf/+PwfvPL5K3xY/CEAo3qP4taTb8Xr8vL7935fq6krw5vB3DPnJrVOFkxMs7R1s1ZnFL5vlGgiQro3vemMpkMpKi3iH1v+wSubX2Ft8VoARvYayeyTZzNl2BSGdhsaydsrs5f15jLtT2do1jKmIyouLXYCyOevsKZoDQAjeo1g1rdnMWX4FI7odkTM/aYdM41px0xrdAr6RLNgYhpkzVrGHHrFpcUs3rKYVz5/hdVFzsTpx/Q8hlu+fQtThk/hW92+1cY1jM2CiYkp3KxV7iu3Zi1jkuyrsq8iAeSDnR8ATgC5+aSbmTJ8Ckd2P7KNa9g0CyamnuhmrS6pzRuEaIxpma/Lvq4VQBTl6B5Hc9NJNzF1+NQOEUCiWTAxEarK3sq97CrfRUZKRps/ctSYzuab8m+cALL5Fd7f+T6KclSPo7hx4o1MGT6FYT2GtXUVW82+LQxgvbWMSZZwAHn181dZVbgKRRneYzg3TLyBKcOnMLzH8LauYkJYMDEJ6a0VPbFcv+x+zD55NtOOmZbgmhrTMewq38Xirc4VSDiADOs+jOsnXM+U4VM4qudRbV3FhEtqMBGRycCDOM+A/x9VnVdn+yDgaaBrKM9sVV0sItOBm6OyjgHGqeo6ESnAefJjeETOJFX9JpnH0VmpKnsq9rC7YndczVp1J5bbWbqTW5beAmABxRw2dlfsjtwDWVW4iqAGObL7kVw34TqmDp/aKQNItKQFExFxAw8DZwOFwGoReVlVN0Zlux14TlUfFZEROM+LH6KqC4AFoXJGAy+p6rqo/aaHngVvWskX8PFV2VcJadaKNbFcpb+SX6/4NcO6DyMrJYvs1GyyUrJIdadaE5rpNPZU7IlcgawsXElQg3yr27f4xfhfMPWoqRzV46jD5u89mVcm44GtqroNQEQWAucC0cFEgXB3oRygKEY5FwPPJrGeh51ED0IsKo31z+b8Upu8YHKtNK/LGwkumd7MSJDJTol6T3XeI2kx8mamZB62k/mZtrWnYg+vbX2NVz5/hfd2vEdQgxzR7QiuGX8NU4dP5eieRx82ASRaMoNJf2BH1HohcGKdPHcBb4jINUAmcFaMci7ECULRnhSRAPACcLfGmqzI1BNu1tpVsYvMlMyE9Nb6bPdneFwefEFfvW09M3ryu7N+R2lNKWU1ZZH3suqyWmm7K3bzr33/iqxX+aua9dlZKVmkkUa3Dd1qXf00FJxirWelZLVq1uF42T2mjmVv5V5e23IwgAQ0wNCuQ5k5fiZTh0/lmJ7HHJYBJJok63tYRH4IfEdVrwyt/wQYr6rXROW5IVSH/xaRicDjwChVZy5wETkR517L6Kh9+qvqThHJxgkmf1XVv8T4/BnADIDc3NzjFy5cmJTjPJTKysrIymrd86kVxR9wplmPPAkxDgEN8ELhCzz95dN4xINf/fj0YEBJdaVy3bDrOLP3mS0u2x/0UxGooDJQSUWgggp/BeWB8shyRcB5lfvLKa0upVqqnbwx8sWa0LAur3jJ8GSQ6c4kw51BhifDeQ8tZ7ozSXen19qW6c48mC/0nuZKa9YXyvJvlvPAlgeoDlYn5HzVVVVeRVpm538IVEu05pwc8B3g3T3vsmLXCtbtX0eQIP3S+nFar9M4teepHJF5RLsPIEEN4nV5Y17FN+f75PTTT1+rqnnN+axkBpOJwF2q+p3Q+q0AqnpPVJ4NwGRV3RFa3wZMCN9QF5H7gV2q+psGPuMyIE9VZzZWl7y8PF2zpuPfYikoKCA/P7/F+1X4KiJPI0zEBID/2vcvrltyHWuK1vDdI7/LvLPm8daXb7XJL+0Nqzcw8oSRMbepKhW+ioNXQdWllNaUUl5TXvtqqc6VUvR6+FUdqI75GdFc4oo0wTV2ZfT4R49TUl1Sb//+2f354KoPknpODlfNPSd7K/eyZOsSXvn8Fd7Z/g4BDTCk6xCmDJ/C1OFTGdlrZLsPINEam5urOd8nItLsYJLMZq7VwDARGQrsBC4CflQnz3bgTOApETkGSAN2AYiIC/ghcGo4s4h4gK6qultEvMAUYFkSj6FDS3SzVlCD/GX9X7j7rbvxur38YfIfmHbMNEQkMrFceyIiZKZkJmSSu2p/NeW+8khAaizwRKeXVJdQWFoYWS/3lTf4GTtLd3LG02fQN6svfbP7Rt77ZfeLLGen2BigRNtXuY8lXyzhlc2v8M6Od/AH/QzJGcJP837K1KM6XgBpK0kLJqrqF7rHtZ8AACAASURBVJGZwBKcbr9PqOoGEZkDrFHVl4EbgcdE5Hqcm/GXRd3/OBUoDN/AD0kFloQCiRsnkDyWrGPoyKJ7a3VJ7RL3f4adpTu5ccmNvL39bU4bfBr3TrqXftn9ElTb9i/Vk0qqJ5Xu6d3jKicQDDDhfyZQVFa/00KmN5Mjuh1BcWkxG3dvZFf5rnrNdJneTCe4hINNVt/a69l9Yz7vxNS2v2p/5Ark7e1v4w/6GZwzmP88/j+ZOnwqo3qPsgDSQkkdZ6Kqi3G6+0an3RG1vBH4dgP7FgAT6qSVA8cnvKKdTHlNOUWlRU6zS5y9tVSV/9v4f9zx5h0ENMC8s+bx49E/tv9oreR2ubn1lFtrjcsBSPekM++sebWu7moCNXxT/g3FpcUUlRZRXHbwvbi0mM93f87X5V/XCzhprjT6b+gfCTB1g02/rH50Tet62P0b7q/az5IvlvDq5ld5a/tb+IN+BuUMYsa4GUw9aiqje48+7M5JItkI+E4kMgixcjcZ3vjn1tpVvotZy2ax5IsljO8/nvu/cz9Dug5JTGUPY+GA0dQ9phR3CgO6DGBAlwENluUL+PimonbA+XTrp9Rk1lBUWsQ729/h6/KvI8+3D0vzpNVqTosOOP2y+9Evux/d0rp1+C/XkqoSlnyxhGc/fZaP3v0IX9DHwC4DuWrcVUwdPpUxuWM6/DG2FxZMOolagxAT0K7+6uevMnvZbCp8Ffzq1F9x1bircLvcCaqtSdQ9Jq/bS//s/vTP7h9J2xCsfbPZH/Szq3zXwaua0JVN+EpnVeEqvir7ioAGapWd6k49GHBCVzR1g0/39O7tbrxPSVUJb2x7g1c2v8JbX76FL+gjNzWXK467gqlHTWVs7lgLIElgwaQTSGSz1r7KffzqzV+x6LNFjMkdw4OTH+w0E9EdrjwuTyQgNCQQDLC7YnetZrToZrXVO1fzVdlX9cYTpbhT6JPVp1agqdtpoGdGz6QHnAPVB3jjizd45fNXWPHvFfiCPvpn9+eK465gyvApeHd4GTV+VFLrcLizYNKBJbpZ65//+ic3v3Ezuyt3c9PEm5g5fqY9XfEw4Xa5yc3KJTcrl+M4LmaeoAbZXbE7EmhqBZzSYj4s/pDismJqAjW19vO6vPTJ6tNop4FeGb0avfKNNcjz7CPOPhhAvlxBTaCGftn9+H/H/T+mDJ/CcX2Oi1yBbCjckLiT1UFU+6vxB/2H7CrMgkkH5Qv4KC4rpspfFXezVllNGXNWzGHBJws4qsdRPHnek4zJHZPA2prOwCUuemf2pndmb8YyNmYeVWVP5Z56gaaozHlf//V6lmxdQlWg9iwHHpeH3MzcmFc3m3dv5pE1j0RmRthZupNrX78WQQhogH7Z/bjs2MuYMmwK4/qOO6ybsGoCNZFgnuHJoFdOL9I98Y8taw4LJh1QdLNWVkrrRsSHrdyxkuuXXE/hgUJ+lvczbjzpRtI8NnratI6I0DOjJz0zejI6d3TMPKrKvqp9tXuoRV3tbNi1gaXbljY6rU5Qg2R5s1hwwQLG9R3X7u7bHEr+oJ9qfzVBDZLuTadPZp82ebidBZMOZnf57oQ0a1X6Kvntu7/lfz78HwbnDGbRhYs4of8JCaypMbGJCN3Tu9M9vTujese+j6Gq7K/aT3FZMWc/c3bMPOW+cvL6NWtwdqcTCAao8lcR1CCp7lR6Z/Ymw5vRps3SFkw6CF/AR02ghr1Ve+Nu1vqo+COuff1avtj3BZeOvZTbT72dDG9GAmtrTHxEhG7p3eiW3o3+2f3ZWbqzXp7DadAsOFdjVf4qAsEAXpeXnhk9yUzJbJOJSmOxYNIBhJu1FI2rWasmUMMDqx7goQ8eondmb5694FlOHXxq0zsa04Zmnzw75iDP2SfPbsNaHRqqSpW/Cn/Qj8floWtqV7JS2+dzgSyYtGNBDbKnYg97KveQ4c2Iq114065NXPv6tWzYtYEfjvghv87/NTlpOQmsrTHJ0dxBnp2FqlIdqMYX8OESFzlpOWSnZJPmad6s1G3Fgkk75Qv4KCotojpQHVezViAY4NE1j3Lve/eSk5bDE99/gu8c+Z0E19ZRE6ih2l+NICDOf4rwMgrOokSCoohE1sPL0e/GhLXHiUQTrdrvBBARITslmy5ZXUjzpHWYzgUWTNqhsuoyisuK4+6ttW3fNq59/Vo+LP6Q7w37HvPOnEePjB4JrKkjqEHKa8pJdacyMGcgHpcHVSWoQRRFVSPv/qDzTJXwK3o9oIFInugAFCsogbMc/uxYwcglLgtQpl0Ld+VVdZqwe2f2Js2T1iFnm7Bg0o7UbdZqbW+toAZ5et3T3P323aS6U3nouw9x3tHnJeXLtNJXSSAYoHdmb3LSchL2Kyo6AMUKSuG0QlchvTN7E9AAgWCgXqAKB6ggQQLBQL2gVDdQKRozMDUWqIxpCV/AR7W/GkXbtCtvonXs2nciiWrWKjxQyA1LbuDdHe9y+pDTuXfSvfTJ6pPg2jr1rfRVkp2aTe/M3gnvkhj+4kbATcO/0sJtys0RHYwaClRBDUbSg+oEoIDWDlKBYAC/+gkSJBgMNnn1FJ0WDkLhY3SJC4/L02GaMkzr1O3Km5uV2+ZdeRPNgkk7UFZdRlFpER63p9XNWqrKcxue446CO1BVfnfW7/jR6B8l/JezqlJeU47H5WFgzsCEPHjqUIkOUInUWFCKTot15RTu7hme9kIQvG4vXpfXrno6uEAwQHWgmmAwiMftaXddeRPNgkkbim7WyvRmtrqd9Jvyb7hl6S0s3baUiQMmct937mNQzqAE1xaq/FX4Aj56pPege0b7my22rYgIbomvjdsf9Ec6MJTXlFPhq4gEIo/Lg9ft7fDNIIeDoAYjc2J5XB66pXUjKyWLFHdKp/9xYH+dbaQmUENxaXHczVovb36ZW5ffSqWvkjtPu5Mrx12Z8C/5QDBAha+CDG8G/bP7k+pJTWj5xpmbyuPykOHNoFt6N1QVX9AXaU4s95VTVlMWaU5zu9ykuFM65I3aziZ6LEhH6sqbaBZM2kAimrX2Vu7l9n/ezkubX+LY3GN5YPIDDOsxLKH1VFUqfc5Asb5ZfclOteePHyoiQoo7hRR3CpkpmfSkJ0ENRmZCqPBVUO5zrmDCTXdel7dTtcG3Z3XHgmSnZNMlrWN15U00CyaHULhZa3fFbrJSslr9q3LZtmXcvPRm9lbu5eaTbmbm+JkJbwKpCdRQ5auiW3o3emb0tF/A7YBLXJFn0YefWxMIBiLdS8PBJRgMUlpditvldprI7P5LwkRm5VXISs0iNzOXdG/6YRtAoiU1mIjIZOBBwA38j6rOq7N9EPA00DWUZ7aqLhaRIcAmYHMo6ypVvTq0z/HAU0A6zvPlr1XV2g/Bboeim7W6pHZp1X/ucn85N71xE89++ixH9ziaZ85/psGJ8loreszIkG5DbAbhds7tcpPuSifdmx7p1bbDs4OBOQOp8lcdvP+i6vSME7fdf2mh6K68Gd4M+mb1JcObYT+w6kjaX5SIuIGHgbOBQmC1iLysqhujst0OPKeqj4rICJzgMCS07QtVPTZG0Y8CM4BVofyTgdeScxSJUVpdSnFpcVzNWu9uf5drPryGXTW7mHnCTG6YeEPC712Ex4zkZuWSk5pjv2Y7KEHI8GaQ4c2ge3r3yP2XmkCNc/+lppwyX1lkRoLw/Rf7dX1Q9LTu4a68mSmZFoQbkcwzMx7YqqrbAERkIXAuEB1MFOgSWs4BihorUET6Al1UdWVo/S/AebTTYBLprVWxh8yU1vXWqvRVcs879/D4R4/TP70/iy5clPBpt8M3eXPScuiZ0dPa3TuZ6PsvWSlZ9MrsRVCDTpON37n/UuGrwK9+VBWXuA7L7snRY0G87vY3K297l8xg0h/YEbVeCJxYJ89dwBsicg2QCZwVtW2oiHwEHABuV9W3Q2UW1imzf6wPF5EZOFcw5ObmUlBQ0OoDaQ1F8QV8KNrqX3ybDmzi95//nsLKQs7tey7Te08nfWc6G3Ym7hGkQQ0iCB6Xh6/kKzZHWhY7hrKyskP+b9vexXNOwrMFhMfCEG5ADl3FdNTgUlVexYbVsf/fhI9TxLlKCw8s3c72Q1zLQyvR/3eSGUxi/dXVvbdxMfCUqv63iEwEnhGRUUAxMEhV94TukbwoIiObWaaTqDofmA+Ql5en+fn5rTyMlotu1mrNPYeaQA33rbyPhz9+mD5ZfVj4g4WcMugUNqzewMgTRiakjuExI70ye9E1rWuHbeIoKCjgUP7bdgSJOifhedJqAjXO/RdfufP0w9D/uI7UPTn6/07drrzd0rq122ndkynR/3eSGUwKgYFR6wOo34x1Bc49D1R1pYikAT1V9RugOpS+VkS+AIaHyhzQRJltJhHNWht2beDa165l0+5NXDjyQu7Kv4suqV2a3rGZoseMDOgywC7hTYNEQqPx3V4yUzLpQY9I92Rf0Od0T64pj3Qfj+6e3B5/nIR/QIkIXVK6kJOWc9iNBUmmZAaT1cAwERkK7AQuAn5UJ8924EzgKRE5BkgDdolIL2CvqgZE5AhgGLBNVfeKSKmITADeBy4B/pjEY2i2mkANRQeK8AV9rRqP4Q/6eWT1I9y38j66pnXlyXOfZNK3JiWsfqoaGZPQL7sfWSlZ9p/ItFikezKpTmeSTOcHii/o9HgKj38JBp3pZdq6e3K1v5qaQA3BYJA0T5p15U2ipAUTVfWLyExgCU633ydUdYOIzAHWqOrLwI3AYyJyPc7F82WqqiJyKjBHRPxAALhaVfeGiv4pB7sGv0Y7uPke3azVmrmqtu7dynWvX8dHX33ElOFTuOfMe+ie3j1h9av2V1Ptr6Z7Rnd6pPfoEM0SpuNwu9y4XW7SPGmR7snR08OU1ZQ54180GJl6JpndkyPP1REhw5NBr8xeFHuKD7vH/B5qSe3npqqLcbrvRqfdEbW8Efh2jP1eAF5ooMw1QGIHV7RSUIPsrtjN3oq9rWrWCmqQJz96kt+88xvSPGk8cs4jnHvUuQmtn40ZMW2hOdPDlFaXOlcrCh63c/XS2h860V15073pzliQTjCte0diZ7qVws1aNYGaVjVr7SjZwfVLrmdl4UrOGHoG9559L7lZuQmrX3gkdJ+sPq0eJGlMojRrepiacir9lZHuyeEJLhtqkoruypviTqF3Zu9ON617R2LBpBVqDUJMbdkgRFVl4acLuWvFXagq9559LxeNuihhX/a+gI8qfxVdUrvYmJHDgM/no7CwkKqqqkhaTk4OmzZtasNatV54Mgs/fqq0CnWeWOYIdU8Op0U/pKxKqihqpC9ORz4nyRJ9TtLS0hgwYABeb+u/LyyYtEBQg+wq38W+yn2tatb6uuxrbl56M8v/tZyJAyZy/3fuZ2DOwKZ3bAZVpdxXjkec54xkeDMSUq5p3woLC8nOzmbIkCGRHySlpaVkZ2e3cc0SJ/JsmNBzY8LjQVoy7qWznZNECJ8TVWXPnj0UFhYydOjQVpdnwaSZ4m3Weumzl/jl8l9S5a9iTv4cLj/u8oT1KKn0VeIP+jv8mBHTclVVVbUCSWfkElfCH2hmDhIRevTowa5du+Iqx4JJM8TTrLW3ci+/XP5LXvn8FY7rcxwPTH6AI7sfmZB6+YN+KnwVZHozGZgz0MaMHKY6cyAxh0Yi/oYsmDRhV/muVg9CfOOLN7hl6S3sr9rPrG/P4mcn/CwhvUvCY0Zc4qJ/dn8bM2KMaXPWHtKEkuoSslOzWxRIDlQf4IYlN3D5S5fTM6Mn/5j+D35x4i8SEkjC/fa7pnVlSNch9sAq0zILFsCQIeByOe8LFsRV3J49ezj22GM59thj6dOnD/3794+s19TUNKuMyy+/nM2bG58T7uGHH2ZBnHU1yWVXJgn29va3uXHJjRSXFXPN+Gu4YeINCWl+CgQDBINBXOJicNfBNmbEtNyCBTBjBlRUOOtffumsA0yf3qoie/Towbp16wC46667yMrK4qabbqqVJ3zz3OWK/dv1ySefbPJzfv7zn7eqfsnW1LEdTuwMJEilr5Lb/3k7Fz1/EameVF666CVmnzw7IYGkwldBlb8Kj9vDoJxBFkhMbNddB/n5pH/ve5CfX/91xRUHA0lYRYWTHit/fr5TZits3bqVUaNGcfXVVzNu3DiKi4uZMWMGeXl5jBw5kjlz5kTynnzyyaxbtw6/30/Xrl2ZPXs2Y8eOZeLEiXzzzTcA3H777TzwwAOR/LNnz2b8+PEcddRRvPfeewCUl5dzwQUXMHbsWC6++GLy8vIigS7azTffzIgRIxgzZgyzZs0C4KuvvuLcc89lzJgxjB07lvfffx+A3/3ud4waNYpRo0bxxz/+scFje+2115g4cSLjxo3jwgsvpLy8vFXnrSOzYJIAa4rWcPYzZ/Pkuie54rgreOPHbzCu77i4y/UFfByoPkCmN5Oh3YbiFrc1aZnWq65uWXqcNm7cyBVXXMFHH31E//79mTdvHmvWrGH9+vUsXbqUjRs31tunpKSE0047jfXr1zNx4kSeeOKJmGWrKh988AG///3vI4Hpj3/8I3369GH9+vXMnj2bjz76qN5+X3/9NYsXL2bDhg18/PHH3HrrrYBz5XP22Wfz8ccfs3btWo455hg++OADFixYwAcffMDKlSt55JFH+Pjjj+sdm9frZd68eSxfvpwPP/yQMWPG8OCDDybqNHYY1swVh2p/NfetvI9H1jxCv+x+PPeD5/j2oHqzw7RYUINU+CrwuJwrERszYpol9Mu9sqExFUOGOE1bdQ0eDEl4Jsy3vvUtTjjhhMj6s88+y+OPP47f76eoqIiNGzcyYsSIWvukp6fz3e9+F4Djjz+et99+O2bZ06ZNi+T597//DcA777wTudIYO3YsI0fWf1xD9+7dcblcXHXVVZxzzjlMmTIFcKZjX7hwIQAej4cuXbrw9ttvc8EFF5CR4fz/O++883jnnXeYNGlSrWN777332LhxIyeddBIANTU1nHzyyS0/YR2cBZNW+vSbT7n2tWv5bM9nXDzqYu487U6yU+MfFFXpqySgAXpm9LQxIyax5s6tfc8EICPDSU+CzMyDk55u2bKFBx98kA8++ICuXbvy4x//uNao/bCUlIPNwm63G7/fH7Ps1NTUennCo+cb4/V6WbNmDUuXLmXhwoU8+uijvPHGG0D97rGNlRd9bKrK5MmTeeaZZ5r8/M7MvqlayB/088CqBzjnf89hb9Venj7vae6ddG/cgcQf9HOg+gBpnjSGdB1C9/TuFkhMYk2fDvPnO1ciIs77/PmtvvneEgcOHCA7O5suXbpQXFzMkiVLEv4ZJ598Ms899xwAn3zyScxmtNLSUg4cOMCUKVO4//77I01hp59+On/6058ACAQCHDhwgFNPPZVFixZRWVlJWVkZL730Eqecckq9Mk866SRWrFjBtm3bAOfezZYtWxJ+fO2dXZm0wNa9W7n2tWtZ9/U6zj3qXO4+4+64p4qvO2YkEVc3xjRo+vRDEjzqGjduHCNGjGDUqFEcccQRfPvb8TcH13XNNddwySWXMGbMGMaNG8eoUaPIycmplaekpIRp06ZRXV1NMBjkvvvuA+Chhx7iqquu4s9//jMej4c///nPjB8/nosvvjjSnPXTn/6U0aNHs3Xr1lpl5ubm8vjjj3PhhRdGukP/5je/YdiwYQk/xvZMmnNp2NHl5eXpmjVrWrTPgk8WcNvy29hesp1+2f04sf+JLN6ymHRvOr858zd8/6jvx12v8IN7uqd3p3t69ybHstgjaus73M/Jpk2bOOaYY2qlHa7zUPn9fvx+P2lpaWzZsoVJkyaxZcsWPB7PYXtOGlP3nMT6WxKRtaqa15zy7MokhgWfLGDGKzOo8DltyztLd/L3z/7OyF4j+eu0v9I7s3dc5YcfnRtu0kr1pCai2sYc1srKyjjzzDPx+/2oauQqwxwadqZjuG35bZFAEm1/1f64A0mFrwJVpW9WXxu9bkwCde3albVr17Z1NQ5bFkxi2F6yPWZ6UWnDz0toSk2ghip/Fd3SutEjo4c9Ac4Y06kktbuQiEwWkc0islVEZsfYPkhE3hSRj0TkYxH5Xij9bBFZKyKfhN7PiNqnIFTmutArvkuFGAblDIqZ3ppnSAc1SFlNGUENMjhnMLlZuRZIjDGdTtKCiYi4gYeB7wIjgItFZESdbLcDz6nqccBFwCOh9N3AVFUdDVwK1O3APV1Vjw29vkl03eeeObfeQMF0TzqzT64XDxtV6aukvKacXhm9GNJ1COne9ERW0xhj2o1k/kQeD2xV1W0AIrIQOBeI7vytQJfQcg44z91U1eh5EDYAaSKSqqrJmfehjumjna6T0b25Zp88m2nHTGvW/v6gn0pfJVkpWfTK7GXPGTHGdHpJ6xosIj8AJqvqlaH1nwAnqurMqDx9gTeAbkAmcJaqro1RztWqelZovQDoAQSAF4C7NcZBiMgMYAZAbm7u8eGpElqqOlDdosGDwWAQBLwub8IHHZaVlZGV1bKHc3V2h/s5ycnJ4cgjaz9sLRAI4HbH7mb+3Kbn+PU7v6awtJAB2QO48+Q7+Y9j/iOuOnz99dfMmjWLDz/8kNTUVAYNGsS8efPa1TiL8DkZNWoUK1asoEePHpx11lksW7asXt6rr76ayZMnc9555zVY3oIFCzjjjDPo27cvADNnzmTmzJkcffTRSTuGRKv7d7J161ZKSkpq5Tn99NPbRdfgWN2U6n7pXww8par/LSITgWdEZJSqBgFEZCTwW2BS1D7TVXWniGTjBJOfAH+p90Gq84H54Iwzae1YhK17t5LuSW+y11WVv4qaQA0903vSLb1bix+k1RyH+5iKWA73c7Jp06Z64ycaGlOx4JMF/GLZLyI9FXeU7uAXy35BWnpa5Gq8pVSVSZMmcemll/LCCy8AsG7dunp1aCzAHQrh+ogIWVlZZGdnR2YGrsvr9ZKent7ouJSFCxeSl5fH8OHDAXj66aeTUu94+f3+BrtH1/03SktL47jjjmv1ZyXzBnwhMDBqfQChZqwoVwDPAajqSiAN6AkgIgOARcAlqvpFeAdV3Rl6LwX+F6c5rc0EggEOVB3A4/IwtOtQemb2TEogMaYp171+HflP5fO9575H/lP59V5XvHRFvS7vFb4Krnjpipj585/K57rXG5+C/s0338Tr9XL11VdH0o499lhOOeUUCgoKOP300/nRj37E6NGjAbjvvvsiU7qHp5QvLy/nnHPOYezYsYwaNYq//e1vAMyePTsyVXzdZ6QAPProo9xyyy2R9aeeeoprrrkGcCZlPP744xk5ciTz58+PWffwFa2qMnPmTEaMGME555wTmfYeYM6cOZxwwgmMGjWKGTNmoKo8//zzrFmzhunTp3PsscdSWVlJfn4+4YHRzz77LKNHj2bUqFGRiSfDn3fbbbcxduxYJkyYwNdff12vTitWrIg8XOy4446jtLQUcKbCHz16NGPHjmX2bOfe7bp165gwYQJjxozh/PPPZ9++fQDk5+fzy1/+ktNOO40HH3yQXbt2ccEFF3DCCSdwwgkn8O677zb8DxqHZAaT1cAwERkqIik4N9hfrpNnO3AmgIgcgxNMdolIV+AfwK2qGjlyEfGISDjYeIEpwKdJPIYGqSoVNc5zRvpl92Ngl4E2+NC0a9WB2LccG0pvjk8//ZTjjz++we0ffPABc+fOZePGjaxdu5Ynn3yS999/n1WrVvHYY4/x0Ucf8frrr9OvXz/Wr1/Pp59+yuTJk9m7dy+LFi2KTBV/++231yv7Bz/4AX//+98j63/729+48MILAXjiiSdYu3Yta9as4Q9/+AN79uxpsI6LFi1i8+bNfPLJJzz22GOR56OA03y1evVqPv30UyorK3n11Vf5wQ9+QF5eHgsWLGDdunWkpx/sWFNUVMSsWbP45z//ybp161i9ejUvvvgi4ATNCRMmsH79ek499VQee+yxenW59957efjhh1m3bh1vv/026enpvPbaa7z44ou8//77rF+/PhJAL7nkEn7729/y8ccfM3r0aH79619Hytm/fz8rVqzgxhtv5Nprr+X6669n9erVvPDCC1x55ZUNnot4JK2ZS1X9IjITWAK4gSdUdYOIzAHWqOrLwI3AYyJyPU4T2GWqqqH9jgR+JSK/ChU5CSgHloQCiRtYBtT/F0kyGzNi2qMHJju/9Btq5hrywBC+LKk/Bf3gnMEUXFaQlDqNHz+eoUOHAs4U8eeff35kxt1p06bx9ttvM3nyZG666SZmzZrFlClTOOWUUyLTolx55ZW1poqP1qtXL4444ghWrVrFsGHD2Lx5c2TOrz/84Q8sWrQIgB07dvDFF18wZMiQmHV86623uPjii3G73fTr148zzoiMRODNN9/kd7/7HRUVFezdu5eRI0cyderUBo939erV5Ofn06tXLwCmT5/OW2+9xXnnnUdKSkrkOI4//niWLl1ab/9vf/vb3HDDDUyfPp1p06YxYMAAli1bxuWXXx6ZCr979+6UlJSwf/9+TjvtNAAuvfRSfvjDH0bKCQdVgGXLltWa9PLAgQORK55ESuq3oKouBhbXSbsjankjUG/GN1W9G7i7gWIb/hmUZEENUl5TToo7hcE5g62rr+lQ5p45t9Y0QQAZ3gzmntn6KehHjhzJ888/3+D2ulO1xzJ8+HDWrl3L4sWLufXWW5k0aRJ33HEHH3zwAcuXL2fhwoU89NBDLF26NHIV9P3vf585c+Zw4YUX8txzz3H00Udz/vnnIyIUFBSwbNkyVq5cSUZGBvn5+VQ38QCwWPdEq6qq+NnPfsaaNWsYOHAgd911V8xp86M11qHJ6/VGPqeh6fVnz57NOeecw+LFi5kwYQLLli1DVVs8U0b0eQ8Gg6xcubLWFRSQ8IBic5w3U3jMSO/M3gzuaoHEdDzTR09n/tT5DM4ZjCAMzhnM/KnzW33zHeCMM86gurq6vQEefgAACwJJREFUVpPN6tWrWbFiRb28p556Ki+++CIVFRWUl5ezaNEiTjnlFIqKisjIyODHP/4xN910Ex9++CFlZWWUlJTwve99jwceeIB169bhdrtZt24d69atizxdcdq0abz44os8++yzkV/jJSUldOvWjYyMDD777DNWrVrV6DGceuqpLFy4kEAgQHFxMW+++SZAJHD07NmTsrKyWkEzOzs75pfxiSeeyIoVK9i9ezeBQIBnn302cvXQHF988QWjR49m1qxZ5OXl8dlnnzFp0iSeeOIJKkLPodm7dy85OTl069Yt8vCwZ555psHPmTRpEg899FBkPdajjBPB2meaobS6lOzUbHpn9sbr9rZ1dYxptemjp8cVPOoSERYtWsR1113HvHnzSEtLY8iQITzwwAPs3LmzVt5x48Zx2WWXMX6802fmyiuv5LjjjmPJkiXcfPPNuFwuvF4vjz76KKWlpZx77rlUVVWhqtx///0xP79bt26MGDGCjRs3RsqdPHkyf/rTnxgzZgxHHXUUEyZMaPQYzj//fP75z38yevRohg8fHvlS7tq1K1dddRWjR49myJAhtZ4aedlll3H11VeTnp7OypX/v727j5GqOuM4/v0V9sUuKohiiGsqRNK4FlS6EKMUtVYt26a00bQa0xJLqljaaJu00ZoYTY1gXyzSmlhaSrC2vtSXakxspQq2VCoqrrCoFKw0RZFFLCpFrOjTP84zy3VmEOqdZZi9zyeZzL1nzr1zzrN758y59845y/rSR44cyaxZszjttNMwM7q6upg6depex3POnDksXryYQYMG0dHRwZQpU2hpaaG7u5vOzk6am5vp6uri2muvZeHChcyYMYPt27czevRoFixYUHWfc+fOZebMmYwbN46dO3cyefLkvrlbaimGoN+D3m29tDW30dbctufM/azot8FWU/SYxBD0eydiUimGoN/HRgyp+dBfIYQw4MQ1kxBCCLlFYxJCgyvCqerQv2rxPxSNSQgNrLW1lS1btkSDEj4wM2PLli20trbm2k9cMwmhgbW3t7NhwwY2b97cl7Zjx47cHwwDTcSkUjYmra2ttLe359pfNCYhNLCmpqa+X5iXLFmyJNeAfQNRxKRSrWMSp7lCCCHkFo1JCCGE3KIxCSGEkFshfgEvaTNQOVxq4zkUeKXehdjPREwqRUwqRUwq7U1MPmJmh+3NzgrRmAwUkp7Y26ENiiJiUiliUiliUqnWMYnTXCGEEHKLxiSEEEJu0Zg0luqTWRdbxKRSxKRSxKRSTWMS10xCCCHkFj2TEEIIuUVjEkIIIbdoTOpM0q8k9UrqyaQdImmRpLX+PMzTJWmupHWSVkoan9lmmudfK2laPepSC5KOlLRY0rOSVku6xNMLGxMASa2Slkt62uNytaePkvSY1/F2Sc2e3uLr6/z1ozL7utzT10g6qz41qg1JgyQ9Jel+Xy90PAAkrZe0SlK3pCc8rf+PHzOLRx0fwGRgPNCTSfsBcJkvXwZc58tdwAOAgBOBxzz9EOAf/jzMl4fVu24fMB4jgfG+fCDwd6CjyDHx+ggY4stNwGNe3zuAcz39JuBiX/46cJMvnwvc7ssdwNNACzAKeB4YVO/65YjLt4HfAvf7eqHj4XVaDxxaltbvx0/0TOrMzP4MvFqWPBVY6MsLgc9n0m+25G/AUEkjgbOARWb2qpn9G1gEfLr/S197ZrbRzFb48hvAs8ARFDgmAF6/bb7a5A8DPgnc6enlcSnF607gdEny9NvM7C0zewFYB0zcB1WoOUntwGeAX/q6KHA89qDfj59oTPZPh5vZRkgfrkBpIvojgH9l8m3wtN2lNzQ/FXEC6Vt44WPip3S6gV7Swf08sNXMdnqWbB376u+vvwYMZ2DFZQ7wXeBdXx9OseNRYsCDkp6UdKGn9fvxE/OZNBZVSbP3SW9YkoYAdwGXmtnr6Utk9axV0gZkTMzsHeB4SUOBe4BjqmXz5wEdF0mfBXrN7ElJp5aSq2QtRDzKnGxmL0kaASyS9Nz75K1ZXKJnsn/a5F1N/LnX0zcAR2bytQMvvU96Q5LURGpIfmNmd3tyoWOSZWZbgSWkc9xDJZW+FGbr2Fd/f/1g0unUgRKXk4HPSVoP3EY6vTWH4sajj5m95M+9pC8dE9kHx080Jvun+4DS3RPTgHsz6V/xOzBOBF7zLusfgTMlDfO7NM70tIbj57HnA8+a2fWZlwobEwBJh3mPBEkHAJ8iXU9aDJzj2crjUorXOcDDlq6s3gec63c3jQLGAMv3TS1qx8wuN7N2MzuKdEH9YTM7n4LGo0RSm6QDS8uk//se9sXxU+87D4r+AG4FNgJvk74NTCedy30IWOvPh3heATeSzpWvAjoz+/kq6eLhOuCCetcrRzwmkbrTK4Fuf3QVOSZel3HAUx6XHuBKTx9N+vBbB/wOaPH0Vl9f56+PzuzrCo/XGmBKvetWg9icyq67uQodD6//0/5YDVzh6f1+/MRwKiGEEHKL01whhBByi8YkhBBCbtGYhBBCyC0akxBCCLlFYxJCCCG3aEzCgCBpuI+S2i3pZUkvZtab93IfCyR9dA95Zko6vzal3j9IWirp+HqXIzS2uDU4DDiSrgK2mdmPytJF+p9/t+qGBSVpKfANM+uud1lC44qeSRjQJB0tqUfSTcAKYKSkeZKeUJoX5MpM3qWSjpc0WNJWSbOV5g9Z5uMcIekaSZdm8s9WmmdkjaSTPL1N0l2+7a3+XhXf/CVNkPSID8j3gKTDJTX5+iTP80PtmrvkakmPl+rjjWOpHNdL+oukZyR1SrpHaR6KqzJxWC3p10pzXdzhv6QvL9MUr+8Kpfk/2jLleEZpzovravpHCgNCNCahCDqA+WZ2gpm9SJrXoRM4DjhDUkeVbQ4GHjGz44BlpF8DVyMzmwh8Byg1TN8EXvZtZ5NGPn7vRlILcANwtpl9HLgF+L6ZvQ1cAMyTdCZpzKlrfLMbzGwCMNbLlx0S/E0z+wRpKJrfAzM834WlYVg8Djea2VhgB3BRWZlGkOa6ON3MxpN+bX+JpMNJoxAca2bjgFm7iUUosGhMQhE8b2aPZ9bPk7SC1FM5hvQhW+5NM3vAl58EjtrNvu+ukmcSafBBzKw0rEW5Y4BjgT8pDSt/GT6wnpmt9O3vJQ1j8bZvc7qk5aShMk7x7Uvu8+dVwCoz22RmO0gTJbX7ay9YmrMCUuM1qaxMJ5Fi8aiX6Xyv06ukYd5/IekLwH92E4tQYDEEfSiCvg8/SWOAS4CJZrZV0i2kcZvK/Tez/A67P1beqpJnt+PlZwhY6b2Jaj5GmnOjdHrtw8DPSLNQvijpmrJyl8rxbma5tF4qV/kF0vJ1AX8wsy9XFFbqBM4gDap4MWngvxD6RM8kFM1BwBvA69o1o1ytLQW+CCBpLNV7Ps8AR0ia6PmaJR3ry18ChpAGMLxR0kHAAaSG4RUfFfbsD1CuUZIm+PJ5Xs6sR4FTJI32crRJGuPvd5CZ3Q98iyqn7UKInkkomhWkD/Ie0rzWf+2H9/gpcLOklf5+PaReRh8ze0vSOcBc/7AeDPxY0mbSNZJTvQfyc+AnZjZd0kLf1z9Js0/+v1YDX5M0H3gOmFdWpk2SpgO3Z26n/h7wJnC3X+f5EGne9RDeI24NDqHGlCZfGmxmO/y02oPAGNs1nWw9ynQ0cKeZxe9JQr+InkkItTcEeMgbFQEX1bMhCWFfiJ5JCCGE3OICfAghhNyiMQkhhJBbNCYhhBByi8YkhBBCbtGYhBBCyO1/BNTIIJXptSQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "skplt.estimators.plot_learning_curve(Rtree_clf_1,RF_tree_featuresTrain,df_trainlabel)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Accuracy: 0.8974564089280319\n",
      "Test Accuracy: 0.8937902952154734\n"
     ]
    }
   ],
   "source": [
    "# Train Accuracy\n",
    "print('Train Accuracy:',cross_val_score(Rtree_clf_1,RF_tree_featuresTrain,df_trainlabel,cv=5).mean())\n",
    "\n",
    "# Test Accuracy\n",
    "Rtree_clf_1 = Rtree_clf_1.fit(RF_tree_featuresTrain, df_trainlabel)\n",
    "y_pred = Rtree_clf_1.predict(RF_tree_featuresTest)\n",
    "ac_score = accuracy_score(y_pred, df_testlabel)\n",
    "print('Test Accuracy:', accuracy_score(y_pred,df_testlabel))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.893790\n",
      "Confusion matrix, without normalization\n",
      "[[537   0   0   0   0   0]\n",
      " [  0 406  85   0   0   0]\n",
      " [  0  64 467   1   0   0]\n",
      " [  0   0   0 476   8  12]\n",
      " [  0   0   0  22 350  48]\n",
      " [  0   0   0  63  10 398]]\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Confusion Matrix\n",
    "cf_mat = confusion_matrix(df_testlabel,y_pred)\n",
    "print('Accuracy: %f' %ac_score)\n",
    "activities = le.classes_\n",
    "\n",
    "#Plotting Confusion matrix heatmap\n",
    "def plot_confusion_matrix(cm,classes, normalize=False,\n",
    "                         title='Confusion matrix',\n",
    "                         cmap=plt.cm.Blues):\n",
    "    if normalize:\n",
    "        cm = cm.astype('float')/cm.sum(axis=1)[:,np.newaxis]\n",
    "        print(\"Normalized confusion matrix\")\n",
    "    else:\n",
    "        print('Confusion matrix, without normalization')\n",
    "    \n",
    "    print(cm)\n",
    "    \n",
    "    plt.imshow(cm, interpolation='nearest', cmap=cmap)\n",
    "    plt.title(title)\n",
    "    plt.colorbar()\n",
    "    tick_marks= np.arange(len(classes))\n",
    "    plt.xticks(tick_marks,classes, rotation=45)\n",
    "    plt.yticks(tick_marks,classes)\n",
    "    \n",
    "    fmt = '.2f' if normalize else 'd'\n",
    "    thresh = cm.max()/2.\n",
    "    for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n",
    "        plt.text(j, i, format(cm[i, j], fmt),\n",
    "                 horizontalalignment=\"center\",\n",
    "                 color=\"white\" if cm[i, j] > thresh else \"black\")\n",
    "\n",
    "    plt.ylabel('True label')\n",
    "    plt.xlabel('Predicted label')\n",
    "    plt.tight_layout()\n",
    "\n",
    "plot_confusion_matrix(cf_mat, classes=activities,title=\"Confusion Matrix for Test data\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimal number of features : 26\n"
     ]
    },
    {
     "ename": "ValueError",
     "evalue": "Image size of 386x104000 pixels is too large. It must be less than 2^16 in each direction.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/IPython/core/formatters.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, obj)\u001b[0m\n\u001b[1;32m    339\u001b[0m                 \u001b[0;32mpass\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    340\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 341\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mprinter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    342\u001b[0m             \u001b[0;31m# Finally look for special method names\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    343\u001b[0m             \u001b[0mmethod\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_real_method\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprint_method\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/IPython/core/pylabtools.py\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m(fig)\u001b[0m\n\u001b[1;32m    242\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    243\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;34m'png'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mformats\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 244\u001b[0;31m         \u001b[0mpng_formatter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfor_type\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mFigure\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mlambda\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mprint_figure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'png'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    245\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;34m'retina'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mformats\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0;34m'png2x'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mformats\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    246\u001b[0m         \u001b[0mpng_formatter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfor_type\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mFigure\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mlambda\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mretina_figure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/IPython/core/pylabtools.py\u001b[0m in \u001b[0;36mprint_figure\u001b[0;34m(fig, fmt, bbox_inches, **kwargs)\u001b[0m\n\u001b[1;32m    126\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    127\u001b[0m     \u001b[0mbytes_io\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mBytesIO\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 128\u001b[0;31m     \u001b[0mfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprint_figure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbytes_io\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    129\u001b[0m     \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbytes_io\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetvalue\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    130\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mfmt\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'svg'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/matplotlib/backend_bases.py\u001b[0m in \u001b[0;36mprint_figure\u001b[0;34m(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, **kwargs)\u001b[0m\n\u001b[1;32m   2080\u001b[0m                     \u001b[0morientation\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0morientation\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2081\u001b[0m                     \u001b[0mbbox_inches_restore\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0m_bbox_inches_restore\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2082\u001b[0;31m                     **kwargs)\n\u001b[0m\u001b[1;32m   2083\u001b[0m             \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2084\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0mbbox_inches\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mrestore_bbox\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_agg.py\u001b[0m in \u001b[0;36mprint_png\u001b[0;34m(self, filename_or_obj, metadata, pil_kwargs, *args, **kwargs)\u001b[0m\n\u001b[1;32m    525\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    526\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 527\u001b[0;31m             \u001b[0mFigureCanvasAgg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    528\u001b[0m             \u001b[0mrenderer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_renderer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    529\u001b[0m             \u001b[0;32mwith\u001b[0m \u001b[0mcbook\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_setattr_cm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdpi\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdpi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;31m \u001b[0m\u001b[0;31m\\\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_agg.py\u001b[0m in \u001b[0;36mdraw\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    384\u001b[0m         \u001b[0mDraw\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mfigure\u001b[0m \u001b[0musing\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    385\u001b[0m         \"\"\"\n\u001b[0;32m--> 386\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrenderer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_renderer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcleared\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    387\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mRendererAgg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlock\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    388\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_agg.py\u001b[0m in \u001b[0;36mget_renderer\u001b[0;34m(self, cleared)\u001b[0m\n\u001b[1;32m    397\u001b[0m                           and getattr(self, \"_lastKey\", None) == key)\n\u001b[1;32m    398\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mreuse_renderer\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 399\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrenderer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mRendererAgg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mw\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mh\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdpi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    400\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_lastKey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    401\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0mcleared\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_agg.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, width, height, dpi)\u001b[0m\n\u001b[1;32m     84\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwidth\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mwidth\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     85\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mheight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mheight\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 86\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_renderer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_RendererAgg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwidth\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mheight\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdpi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     87\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_filter_renderers\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     88\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Image size of 386x104000 pixels is too large. It must be less than 2^16 in each direction."
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Applying RFECV with svm classifier\n",
    "svc=SVC(kernel=\"linear\")\n",
    "rfecv = RFECV(estimator=svc, step=1, cv=StratifiedKFold(2), # Stratified fold inorder to reduce bias\n",
    "              scoring='accuracy')\n",
    "rfetrain=rfecv.fit(RF_tree_featuresTrain, df_trainlabel)\n",
    "print('Optimal number of features :', rfecv.n_features_)\n",
    "\n",
    "\n",
    "# Plot showing the Cross Validation score\n",
    "plt.figure()\n",
    "plt.xlabel(\"Number of features selected\")\n",
    "plt.ylabel(\"Cross validation score (nb of cordata:image/png;base64,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rect classifications)\")\n",
    "plt.plot(range(1, len(rfecv.grid_scores_) + 1), rfecv.grid_scores_)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Accuracy: 0.920985274742252\n",
      "Test Accuracy: 0.9093993892093655\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Applying RFE with optimal number of features\n",
    "rfe = RFE(estimator=svc, n_features_to_select=rfecv.n_features_, step=1)\n",
    "rfe = rfe.fit(RF_tree_featuresTrain, df_trainlabel)\n",
    "\n",
    "rfe_train=RF_tree_featuresTrain.loc[:,rfe.get_support()]\n",
    "rfe_test=RF_tree_featuresTest.loc[:,rfe.get_support()]\n",
    "\n",
    "skplt.estimators.plot_learning_curve(svc,rfe_train,df_trainlabel)\n",
    "\n",
    "#Checking the Accuracy after rfe\n",
    "# Train Accuracy\n",
    "print(\"Train Accuracy:\", cross_val_score(svc,rfe_train,df_trainlabel, cv=5).mean())\n",
    "#Test Accuracy\n",
    "svc = svc.fit(rfe_train,df_trainlabel)\n",
    "y_pred = svc.predict(rfe_test)\n",
    "print('Test Accuracy:', accuracy_score(y_pred,df_testlabel))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Accuracy: 0.9207125203451971\n",
      "Test Accuracy: 0.9097387173396675\n"
     ]
    }
   ],
   "source": [
    "# Variance threshold\n",
    "selector = VarianceThreshold(0.95*(1-.95))\n",
    "varsel=selector.fit(rfe_train)\n",
    "rfe_train.loc[:,varsel.get_support()].shape\n",
    "vartrain = rfe_train.loc[:, varsel.get_support()]\n",
    "vartest = rfe_test.loc[:,varsel.get_support()]\n",
    "\n",
    "#Checking Accuracy after Variance threshold\n",
    "# Train Accuracy\n",
    "print('Train Accuracy:',cross_val_score(svc,vartrain,df_trainlabel,cv=5).mean())\n",
    "\n",
    "# Test Accuracy\n",
    "scv = svc.fit(vartrain, df_trainlabel)\n",
    "y_pred = scv.predict(vartest)\n",
    "print(\"Test Accuracy:\", accuracy_score(y_pred, df_testlabel))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'cumulative explained variance')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# PCA\n",
    "pca = PCA(n_components=len(vartrain.columns))\n",
    "pca_traindata = pca.fit(vartrain)\n",
    "\n",
    "pca_traindata.explained_variance_\n",
    "pca_traindata.n_components_\n",
    "pcatrain = pca_traindata.transform(vartrain)\n",
    "pcatest = pca_traindata.transform(vartest)\n",
    "cum_ratio = (np.cumsum(pca_traindata.explained_variance_ratio_))\n",
    "\n",
    "# Visualize PCA result\n",
    "plt.plot(np.cumsum(pca_traindata.explained_variance_ratio_))\n",
    "plt.xlabel('number of components')\n",
    "plt.ylabel('cumulative explained variance')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.59920579, 0.80321739, 0.84423994, 0.88029215, 0.910895  ,\n",
       "       0.93124937, 0.94509593, 0.9575934 , 0.9672914 , 0.97486918,\n",
       "       0.98037073, 0.98557434, 0.98994562, 0.99258987, 0.99468547,\n",
       "       0.99627957, 0.99726901, 0.99811571])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 18 features - constant after that\n",
    "pca = PCA(n_components = 18)\n",
    "pca_traindata = pca.fit(vartrain)\n",
    "\n",
    "pca_traindata.explained_variance_\n",
    "pca_traindata.n_components_\n",
    "pcatrain = pca_traindata.transform(vartrain)\n",
    "pcatest = pca_traindata.transform(vartest)\n",
    "(np.cumsum(pca_traindata.explained_variance_ratio_))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f86e49941d0>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# PCA in 2D projection\n",
    "skplt.decomposition.plot_pca_2d_projection(pca,vartrain,df_trainlabel)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Accuracy: 0.9223440658979756\n",
      "Test Accuracy: 0.9107567017305734\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Checking Accuracy after applying PCA\n",
    "skplt.estimators.plot_learning_curve(svc,pcatrain,df_trainlabel)\n",
    "\n",
    "# Train Accuracy\n",
    "print('Train Accuracy:',cross_val_score(svc,pcatrain,df_trainlabel,cv=5).mean())\n",
    "\n",
    "# Test Accuracy\n",
    "scv = svc.fit(pcatrain, df_trainlabel)\n",
    "y_pred = scv.predict(pcatest)\n",
    "ac_score = accuracy_score(y_pred, df_testlabel)\n",
    "print('Test Accuracy:', accuracy_score(y_pred,df_testlabel))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.910757\n",
      "Confusion matrix, without normalization\n",
      "[[537   0   0   0   0   0]\n",
      " [  0 380 109   0   0   2]\n",
      " [  0  59 473   0   0   0]\n",
      " [  0   0   0 492   2   2]\n",
      " [  0   0   0   6 379  35]\n",
      " [  0   0   0  41   7 423]]\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Confusion Matrix\n",
    "cf_mat = confusion_matrix(df_testlabel,y_pred)\n",
    "print('Accuracy: %f' %ac_score)\n",
    "activities = le.classes_\n",
    "\n",
    "#Plotting Confusion matrix heatmap\n",
    "def plot_confusion_matrix(cm,classes, normalize=False,\n",
    "                         title='Confusion matrix',\n",
    "                         cmap=plt.cm.Blues):\n",
    "    if normalize:\n",
    "        cm = cm.astype('float')/cm.sum(axis=1)[:,np.newaxis]\n",
    "        print(\"Normalized confusion matrix\")\n",
    "    else:\n",
    "        print('Confusion matrix, without normalization')\n",
    "    \n",
    "    print(cm)\n",
    "    \n",
    "    plt.imshow(cm, interpolation='nearest', cmap=cmap)\n",
    "    plt.title(title)\n",
    "    plt.colorbar()\n",
    "    tick_marks= np.arange(len(classes))\n",
    "    plt.xticks(tick_marks,classes, rotation=45)\n",
    "    plt.yticks(tick_marks,classes)\n",
    "    \n",
    "    fmt = '.2f' if normalize else 'd'\n",
    "    thresh = cm.max()/2.\n",
    "    for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n",
    "        plt.text(j, i, format(cm[i, j], fmt),\n",
    "                 horizontalalignment=\"center\",\n",
    "                 color=\"white\" if cm[i, j] > thresh else \"black\")\n",
    "\n",
    "    plt.ylabel('True label')\n",
    "    plt.xlabel('Predicted label')\n",
    "    plt.tight_layout()\n",
    "\n",
    "plot_confusion_matrix(cf_mat, classes=activities,title=\"Confusion Matrix for Test data\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'C': 10, 'gamma': 0.001, 'kernel': 'linear'}\n"
     ]
    }
   ],
   "source": [
    "# Parameter Tuning using GridScore\n",
    "param_grid = [\n",
    "  {'C': [1, 10, 100, 1000], 'gamma': [0.001, 0.0001], 'kernel': ['linear']},\n",
    "  {'C': [1, 10, 100, 1000], 'gamma': [0.001, 0.0001], 'kernel': ['rbf']},\n",
    " ]\n",
    "svr = SVC()\n",
    "clf = GridSearchCV(svr, param_grid,cv=5)\n",
    "clf.fit(pcatrain,df_trainlabel)\n",
    "print(clf.best_params_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Accuracy: 0.9230237831866018\n",
      "Test Accuracy: 0.9104173736002714\n"
     ]
    }
   ],
   "source": [
    "svr = SVC(kernel=\"rbf\",C=1000,gamma=0.001)\n",
    "print(\"Train Accuracy:\",cross_val_score(svr,pcatrain,df_trainlabel, cv=5).mean())\n",
    "# Test Accuracy\n",
    "scv = svr.fit(pcatrain, df_trainlabel)\n",
    "y_pred = scv.predict(pcatest)\n",
    "print(\"Test Accuracy:\",accuracy_score(y_pred, df_testlabel))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}