Task-2_Clustering.ipynb

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   "source": [
    "# Author : Kritika Srivastava\n",
    "\n",
    "## Task 2 : Prediction using Unsupervised Machine Learning\n",
    "## GRIP @ The Sparks Foundation\n",
    "\n",
    "In this K-means clustering task I tried to predict the optimum number of clusters and represent it visually from the given ‘Iris’ dataset.\n",
    "\n",
    "\n",
    "## Technical Stack  : Scikit Learn, Numpy Array, Scipy, Pandas, Matplotlib"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 1,
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   "outputs": [],
   "source": [
    "from sklearn import datasets\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.cluster import KMeans\n",
    "import matplotlib.patches as mpatches\n",
    "import sklearn.metrics as sm\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from scipy.cluster.hierarchy import linkage,dendrogram\n",
    "from sklearn.cluster import DBSCAN \n",
    "from sklearn.decomposition import PCA "
   ]
  },
  {
   "source": [
    "## Step 1 - Loading the dataset"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 2,
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      "[[5.1 3.5 1.4 0.2]\n [4.9 3.  1.4 0.2]\n [4.7 3.2 1.3 0.2]\n [4.6 3.1 1.5 0.2]\n [5.  3.6 1.4 0.2]\n [5.4 3.9 1.7 0.4]\n [4.6 3.4 1.4 0.3]\n [5.  3.4 1.5 0.2]\n [4.4 2.9 1.4 0.2]\n [4.9 3.1 1.5 0.1]\n [5.4 3.7 1.5 0.2]\n [4.8 3.4 1.6 0.2]\n [4.8 3.  1.4 0.1]\n [4.3 3.  1.1 0.1]\n [5.8 4.  1.2 0.2]\n [5.7 4.4 1.5 0.4]\n [5.4 3.9 1.3 0.4]\n [5.1 3.5 1.4 0.3]\n [5.7 3.8 1.7 0.3]\n [5.1 3.8 1.5 0.3]\n [5.4 3.4 1.7 0.2]\n [5.1 3.7 1.5 0.4]\n [4.6 3.6 1.  0.2]\n [5.1 3.3 1.7 0.5]\n [4.8 3.4 1.9 0.2]\n [5.  3.  1.6 0.2]\n [5.  3.4 1.6 0.4]\n [5.2 3.5 1.5 0.2]\n [5.2 3.4 1.4 0.2]\n [4.7 3.2 1.6 0.2]\n [4.8 3.1 1.6 0.2]\n [5.4 3.4 1.5 0.4]\n [5.2 4.1 1.5 0.1]\n [5.5 4.2 1.4 0.2]\n [4.9 3.1 1.5 0.2]\n [5.  3.2 1.2 0.2]\n [5.5 3.5 1.3 0.2]\n [4.9 3.6 1.4 0.1]\n [4.4 3.  1.3 0.2]\n [5.1 3.4 1.5 0.2]\n [5.  3.5 1.3 0.3]\n [4.5 2.3 1.3 0.3]\n [4.4 3.2 1.3 0.2]\n [5.  3.5 1.6 0.6]\n [5.1 3.8 1.9 0.4]\n [4.8 3.  1.4 0.3]\n [5.1 3.8 1.6 0.2]\n [4.6 3.2 1.4 0.2]\n [5.3 3.7 1.5 0.2]\n [5.  3.3 1.4 0.2]\n [7.  3.2 4.7 1.4]\n [6.4 3.2 4.5 1.5]\n [6.9 3.1 4.9 1.5]\n [5.5 2.3 4.  1.3]\n [6.5 2.8 4.6 1.5]\n [5.7 2.8 4.5 1.3]\n [6.3 3.3 4.7 1.6]\n [4.9 2.4 3.3 1. ]\n [6.6 2.9 4.6 1.3]\n [5.2 2.7 3.9 1.4]\n [5.  2.  3.5 1. ]\n [5.9 3.  4.2 1.5]\n [6.  2.2 4.  1. ]\n [6.1 2.9 4.7 1.4]\n [5.6 2.9 3.6 1.3]\n [6.7 3.1 4.4 1.4]\n [5.6 3.  4.5 1.5]\n [5.8 2.7 4.1 1. ]\n [6.2 2.2 4.5 1.5]\n [5.6 2.5 3.9 1.1]\n [5.9 3.2 4.8 1.8]\n [6.1 2.8 4.  1.3]\n [6.3 2.5 4.9 1.5]\n [6.1 2.8 4.7 1.2]\n [6.4 2.9 4.3 1.3]\n [6.6 3.  4.4 1.4]\n [6.8 2.8 4.8 1.4]\n [6.7 3.  5.  1.7]\n [6.  2.9 4.5 1.5]\n [5.7 2.6 3.5 1. ]\n [5.5 2.4 3.8 1.1]\n [5.5 2.4 3.7 1. ]\n [5.8 2.7 3.9 1.2]\n [6.  2.7 5.1 1.6]\n [5.4 3.  4.5 1.5]\n [6.  3.4 4.5 1.6]\n [6.7 3.1 4.7 1.5]\n [6.3 2.3 4.4 1.3]\n [5.6 3.  4.1 1.3]\n [5.5 2.5 4.  1.3]\n [5.5 2.6 4.4 1.2]\n [6.1 3.  4.6 1.4]\n [5.8 2.6 4.  1.2]\n [5.  2.3 3.3 1. ]\n [5.6 2.7 4.2 1.3]\n [5.7 3.  4.2 1.2]\n [5.7 2.9 4.2 1.3]\n [6.2 2.9 4.3 1.3]\n [5.1 2.5 3.  1.1]\n [5.7 2.8 4.1 1.3]\n [6.3 3.3 6.  2.5]\n [5.8 2.7 5.1 1.9]\n [7.1 3.  5.9 2.1]\n [6.3 2.9 5.6 1.8]\n [6.5 3.  5.8 2.2]\n [7.6 3.  6.6 2.1]\n [4.9 2.5 4.5 1.7]\n [7.3 2.9 6.3 1.8]\n [6.7 2.5 5.8 1.8]\n [7.2 3.6 6.1 2.5]\n [6.5 3.2 5.1 2. ]\n [6.4 2.7 5.3 1.9]\n [6.8 3.  5.5 2.1]\n [5.7 2.5 5.  2. ]\n [5.8 2.8 5.1 2.4]\n [6.4 3.2 5.3 2.3]\n [6.5 3.  5.5 1.8]\n [7.7 3.8 6.7 2.2]\n [7.7 2.6 6.9 2.3]\n [6.  2.2 5.  1.5]\n [6.9 3.2 5.7 2.3]\n [5.6 2.8 4.9 2. ]\n [7.7 2.8 6.7 2. ]\n [6.3 2.7 4.9 1.8]\n [6.7 3.3 5.7 2.1]\n [7.2 3.2 6.  1.8]\n [6.2 2.8 4.8 1.8]\n [6.1 3.  4.9 1.8]\n [6.4 2.8 5.6 2.1]\n [7.2 3.  5.8 1.6]\n [7.4 2.8 6.1 1.9]\n [7.9 3.8 6.4 2. ]\n [6.4 2.8 5.6 2.2]\n [6.3 2.8 5.1 1.5]\n [6.1 2.6 5.6 1.4]\n [7.7 3.  6.1 2.3]\n [6.3 3.4 5.6 2.4]\n [6.4 3.1 5.5 1.8]\n [6.  3.  4.8 1.8]\n [6.9 3.1 5.4 2.1]\n [6.7 3.1 5.6 2.4]\n [6.9 3.1 5.1 2.3]\n [5.8 2.7 5.1 1.9]\n [6.8 3.2 5.9 2.3]\n [6.7 3.3 5.7 2.5]\n [6.7 3.  5.2 2.3]\n [6.3 2.5 5.  1.9]\n [6.5 3.  5.2 2. ]\n [6.2 3.4 5.4 2.3]\n [5.9 3.  5.1 1.8]]\n"
     ]
    }
   ],
   "source": [
    "iris = datasets.load_iris()\n",
    "print(iris.data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "['setosa' 'versicolor' 'virginica']\n"
     ]
    }
   ],
   "source": [
    "print(iris.target_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "[0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2\n 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n 2 2]\n"
     ]
    }
   ],
   "source": [
    "print(iris.target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = iris.data\n",
    "y = iris.target"
   ]
  },
  {
   "source": [
    "## Step 2 - Visualizing the input data and its Hierarchy"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 6,
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "#Plotting\n",
    "fig = plt.figure(1, figsize=(7,5))\n",
    "ax = Axes3D(fig, rect=[0, 0, 0.95, 1], elev=48, azim=134)\n",
    "ax.scatter(x[:, 3], x[:, 0], x[:, 2], edgecolor=\"k\", s=50)\n",
    "ax.set_xlabel(\"Petal width\")\n",
    "ax.set_ylabel(\"Sepal length\")\n",
    "ax.set_zlabel(\"Petal length\")\n",
    "plt.title(\"Iris Clustering K Means=3\", fontsize=14)\n",
    "plt.show()\n",
    "\n",
    "#Hierachy Clustering \n",
    "hier=linkage(x,\"ward\")\n",
    "max_d=7.08\n",
    "plt.figure(figsize=(15,8))\n",
    "plt.title('Iris Hierarchical Clustering Dendrogram')\n",
    "plt.xlabel('Species')\n",
    "plt.ylabel('distance')\n",
    "dendrogram(\n",
    "    hier,\n",
    "    truncate_mode='lastp',  \n",
    "    p=50,                  \n",
    "    leaf_rotation=90.,      \n",
    "    leaf_font_size=8.,     \n",
    ")\n",
    "plt.axhline(y=max_d, c='k')\n",
    "plt.show()"
   ]
  },
  {
   "source": [
    "## Step 3 - Data Preprocessing"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = pd.DataFrame(iris.data, columns=['Sepal Length', 'Sepal Width', 'Petal Length', 'Petal Width'])\n",
    "y = pd.DataFrame(iris.target, columns=['Target'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "   Sepal Length  Sepal Width  Petal Length  Petal Width\n",
       "0           5.1          3.5           1.4          0.2\n",
       "1           4.9          3.0           1.4          0.2\n",
       "2           4.7          3.2           1.3          0.2\n",
       "3           4.6          3.1           1.5          0.2\n",
       "4           5.0          3.6           1.4          0.2"
      ],
      "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>Sepal Length</th>\n      <th>Sepal Width</th>\n      <th>Petal Length</th>\n      <th>Petal Width</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>5.1</td>\n      <td>3.5</td>\n      <td>1.4</td>\n      <td>0.2</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>4.9</td>\n      <td>3.0</td>\n      <td>1.4</td>\n      <td>0.2</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>4.7</td>\n      <td>3.2</td>\n      <td>1.3</td>\n      <td>0.2</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>4.6</td>\n      <td>3.1</td>\n      <td>1.5</td>\n      <td>0.2</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5.0</td>\n      <td>3.6</td>\n      <td>1.4</td>\n      <td>0.2</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "metadata": {},
     "execution_count": 8
    }
   ],
   "source": [
    "x.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "   Target\n",
       "0       0\n",
       "1       0\n",
       "2       0\n",
       "3       0\n",
       "4       0"
      ],
      "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>Target</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "metadata": {},
     "execution_count": 9
    }
   ],
   "source": [
    "y.head()"
   ]
  },
  {
   "source": [
    "## Step 4 - Model Training "
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "KMeans(n_clusters=3)"
      ]
     },
     "metadata": {},
     "execution_count": 11
    }
   ],
   "source": [
    "iris_k_mean_model = KMeans(n_clusters=3)\n",
    "iris_k_mean_model.fit(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "[1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 2 2 2 0 2 2 2 2\n 2 2 0 0 2 2 2 2 0 2 0 2 0 2 2 0 0 2 2 2 2 2 0 2 2 2 2 0 2 2 2 0 2 2 2 0 2\n 2 0]\n"
     ]
    }
   ],
   "source": [
    "print(iris_k_mean_model.labels_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "[[5.9016129  2.7483871  4.39354839 1.43387097]\n [5.006      3.428      1.462      0.246     ]\n [6.85       3.07368421 5.74210526 2.07105263]]\n"
     ]
    }
   ],
   "source": [
    "print(iris_k_mean_model.cluster_centers_)"
   ]
  },
  {
   "source": [
    "## Step 5 - Visualizing the Model Cluster "
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1972460dfd0>"
      ]
     },
     "metadata": {},
     "execution_count": 14
    },
    {
     "output_type": "display_data",
     "data": {
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "plt.figure(figsize=(14,6))\n",
    "\n",
    "colors = np.array(['red', 'green', 'blue'])\n",
    "\n",
    "predictedY = np.choose(iris_k_mean_model.labels_, [1, 0, 2]).astype(np.int64)\n",
    "\n",
    "plt.subplot(1, 2, 1)\n",
    "plt.scatter(x['Petal Length'], x['Petal Width'], c=colors[y['Target']])\n",
    "plt.title('Before classification')\n",
    "plt.legend(handles=[red_patch, green_patch, blue_patch])\n",
    "\n",
    "plt.subplot(1, 2, 2)\n",
    "plt.scatter(x['Petal Length'], x['Petal Width'], c=colors[predictedY])\n",
    "plt.title(\"Model's classification\")\n",
    "plt.legend(handles=[red_patch, green_patch, blue_patch])"
   ]
  },
  {
   "source": [
    "## Step 6 - Calculating the Accuracy and Confusion Matrix"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "0.8933333333333333"
      ]
     },
     "metadata": {},
     "execution_count": 15
    }
   ],
   "source": [
    "sm.accuracy_score(predictedY, y['Target'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "array([[50,  0,  0],\n",
       "       [ 0, 48, 14],\n",
       "       [ 0,  2, 36]], dtype=int64)"
      ]
     },
     "metadata": {},
     "execution_count": 16
    }
   ],
   "source": [
    "sm.confusion_matrix(predictedY, y['Target'])"
   ]
  },
  {
   "source": [
    "In a confusion matrix, the predicted class labels (0, 1, 2) are written along the top (column names). The true class labels (Iris-setosa, etc.) are written along the right side. Each cell in the matrix is a count of how many instances of a true class where classified as each of the predicted classes.\n",
    "&nbsp;\n",
    "\n",
    "## Conclusion\n",
    "### I was  able to successfully carry-out prediction using Unsupervised Machine Learning task and was able to evaluate the model's clustering accuracy score.\n",
    "# Thank You"
   ],
   "cell_type": "markdown",
   "metadata": {}
  }
 ]
}