Projects - Machine Learning/Mushroom - Edible Vs Poisonous.ipynb

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    "# The Data\n",
    "\n",
    "<img src=https://i.imgur.com/IZrcN3s.jpg>\n",
    "\n",
    "## Mushroom Hunting: Edible or Poisonous?\n",
    "\n",
    "\n",
    "This data set includes descriptions of hypothetical samples corresponding to 23 species of gilled mushrooms. Each species is identified as definitely edible, definitely poisonous, or of unknown edibility and not recommended. This latter class was combined with the poisonous one.\n",
    "\n",
    "\n",
    "Attribute Information:\n",
    "\n",
    "1. cap-shape: bell=b,conical=c,convex=x,flat=f, knobbed=k,sunken=s\n",
    "2. cap-surface: fibrous=f,grooves=g,scaly=y,smooth=s\n",
    "3. cap-color: brown=n,buff=b,cinnamon=c,gray=g,green=r, pink=p,purple=u,red=e,white=w,yellow=y\n",
    "4. bruises?: bruises=t,no=f\n",
    "5. odor: almond=a,anise=l,creosote=c,fishy=y,foul=f, musty=m,none=n,pungent=p,spicy=s\n",
    "6. gill-attachment: attached=a,descending=d,free=f,notched=n\n",
    "7. gill-spacing: close=c,crowded=w,distant=d\n",
    "8. gill-size: broad=b,narrow=n\n",
    "9. gill-color: black=k,brown=n,buff=b,chocolate=h,gray=g, green=r,orange=o,pink=p,purple=u,red=e, white=w,yellow=y\n",
    "10. stalk-shape: enlarging=e,tapering=t\n",
    "11. stalk-root: bulbous=b,club=c,cup=u,equal=e, rhizomorphs=z,rooted=r,missing=?\n",
    "12. stalk-surface-above-ring: fibrous=f,scaly=y,silky=k,smooth=s\n",
    "13. stalk-surface-below-ring: fibrous=f,scaly=y,silky=k,smooth=s\n",
    "14. stalk-color-above-ring: brown=n,buff=b,cinnamon=c,gray=g,orange=o, pink=p,red=e,white=w,yellow=y\n",
    "15. stalk-color-below-ring: brown=n,buff=b,cinnamon=c,gray=g,orange=o, pink=p,red=e,white=w,yellow=y\n",
    "16. veil-type: partial=p,universal=u\n",
    "17. veil-color: brown=n,orange=o,white=w,yellow=y\n",
    "18. ring-number: none=n,one=o,two=t\n",
    "19. ring-type: cobwebby=c,evanescent=e,flaring=f,large=l, none=n,pendant=p,sheathing=s,zone=z\n",
    "20. spore-print-color: black=k,brown=n,buff=b,chocolate=h,green=r, orange=o,purple=u,white=w,yellow=y\n",
    "21. population: abundant=a,clustered=c,numerous=n, scattered=s,several=v,solitary=y\n",
    "22. habitat: grasses=g,leaves=l,meadows=m,paths=p, urban=u,waste=w,woods=d"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5c40b09",
   "metadata": {},
   "source": [
    "# Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "98ffbaee",
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5ca566c5",
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  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fb4e7e5e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"../DATA/mushrooms.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d759cd69",
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       "      <th></th>\n",
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       "<p>5 rows × 23 columns</p>\n",
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       "  class cap-shape cap-surface cap-color bruises odor gill-attachment  \\\n",
       "0     p         x           s         n       t    p               f   \n",
       "1     e         x           s         y       t    a               f   \n",
       "2     e         b           s         w       t    l               f   \n",
       "3     p         x           y         w       t    p               f   \n",
       "4     e         x           s         g       f    n               f   \n",
       "\n",
       "  gill-spacing gill-size gill-color  ... stalk-surface-below-ring  \\\n",
       "0            c         n          k  ...                        s   \n",
       "1            c         b          k  ...                        s   \n",
       "2            c         b          n  ...                        s   \n",
       "3            c         n          n  ...                        s   \n",
       "4            w         b          k  ...                        s   \n",
       "\n",
       "  stalk-color-above-ring stalk-color-below-ring veil-type veil-color  \\\n",
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       "2                      w                      w         p          w   \n",
       "3                      w                      w         p          w   \n",
       "4                      w                      w         p          w   \n",
       "\n",
       "  ring-number ring-type spore-print-color population habitat  \n",
       "0           o         p                 k          s       u  \n",
       "1           o         p                 n          n       g  \n",
       "2           o         p                 n          n       m  \n",
       "3           o         p                 k          s       u  \n",
       "4           o         e                 n          a       g  \n",
       "\n",
       "[5 rows x 23 columns]"
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       "(8124, 23)"
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   "id": "2626da1d",
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    {
     "data": {
      "text/plain": [
       "Index(['class', 'cap-shape', 'cap-surface', 'cap-color', 'bruises', 'odor',\n",
       "       'gill-attachment', 'gill-spacing', 'gill-size', 'gill-color',\n",
       "       'stalk-shape', 'stalk-root', 'stalk-surface-above-ring',\n",
       "       'stalk-surface-below-ring', 'stalk-color-above-ring',\n",
       "       'stalk-color-below-ring', 'veil-type', 'veil-color', 'ring-number',\n",
       "       'ring-type', 'spore-print-color', 'population', 'habitat'],\n",
       "      dtype='object')"
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     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
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    "df.columns"
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   "execution_count": 6,
   "id": "6b3e326c",
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     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 8124 entries, 0 to 8123\n",
      "Data columns (total 23 columns):\n",
      " #   Column                    Non-Null Count  Dtype \n",
      "---  ------                    --------------  ----- \n",
      " 0   class                     8124 non-null   object\n",
      " 1   cap-shape                 8124 non-null   object\n",
      " 2   cap-surface               8124 non-null   object\n",
      " 3   cap-color                 8124 non-null   object\n",
      " 4   bruises                   8124 non-null   object\n",
      " 5   odor                      8124 non-null   object\n",
      " 6   gill-attachment           8124 non-null   object\n",
      " 7   gill-spacing              8124 non-null   object\n",
      " 8   gill-size                 8124 non-null   object\n",
      " 9   gill-color                8124 non-null   object\n",
      " 10  stalk-shape               8124 non-null   object\n",
      " 11  stalk-root                8124 non-null   object\n",
      " 12  stalk-surface-above-ring  8124 non-null   object\n",
      " 13  stalk-surface-below-ring  8124 non-null   object\n",
      " 14  stalk-color-above-ring    8124 non-null   object\n",
      " 15  stalk-color-below-ring    8124 non-null   object\n",
      " 16  veil-type                 8124 non-null   object\n",
      " 17  veil-color                8124 non-null   object\n",
      " 18  ring-number               8124 non-null   object\n",
      " 19  ring-type                 8124 non-null   object\n",
      " 20  spore-print-color         8124 non-null   object\n",
      " 21  population                8124 non-null   object\n",
      " 22  habitat                   8124 non-null   object\n",
      "dtypes: object(23)\n",
      "memory usage: 1.4+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9b2dd4d1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "class                       0\n",
       "cap-shape                   0\n",
       "cap-surface                 0\n",
       "cap-color                   0\n",
       "bruises                     0\n",
       "odor                        0\n",
       "gill-attachment             0\n",
       "gill-spacing                0\n",
       "gill-size                   0\n",
       "gill-color                  0\n",
       "stalk-shape                 0\n",
       "stalk-root                  0\n",
       "stalk-surface-above-ring    0\n",
       "stalk-surface-below-ring    0\n",
       "stalk-color-above-ring      0\n",
       "stalk-color-below-ring      0\n",
       "veil-type                   0\n",
       "veil-color                  0\n",
       "ring-number                 0\n",
       "ring-type                   0\n",
       "spore-print-color           0\n",
       "population                  0\n",
       "habitat                     0\n",
       "dtype: int64"
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     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "badc0368",
   "metadata": {},
   "source": [
    "# Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d35789a5",
   "metadata": {},
   "outputs": [
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8119</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8120</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8121</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8122</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8123</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8124 rows × 95 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      cap-shape_c  cap-shape_f  cap-shape_k  cap-shape_s  cap-shape_x  \\\n",
       "0               0            0            0            0            1   \n",
       "1               0            0            0            0            1   \n",
       "2               0            0            0            0            0   \n",
       "3               0            0            0            0            1   \n",
       "4               0            0            0            0            1   \n",
       "...           ...          ...          ...          ...          ...   \n",
       "8119            0            0            1            0            0   \n",
       "8120            0            0            0            0            1   \n",
       "8121            0            1            0            0            0   \n",
       "8122            0            0            1            0            0   \n",
       "8123            0            0            0            0            1   \n",
       "\n",
       "      cap-surface_g  cap-surface_s  cap-surface_y  cap-color_c  cap-color_e  \\\n",
       "0                 0              1              0            0            0   \n",
       "1                 0              1              0            0            0   \n",
       "2                 0              1              0            0            0   \n",
       "3                 0              0              1            0            0   \n",
       "4                 0              1              0            0            0   \n",
       "...             ...            ...            ...          ...          ...   \n",
       "8119              0              1              0            0            0   \n",
       "8120              0              1              0            0            0   \n",
       "8121              0              1              0            0            0   \n",
       "8122              0              0              1            0            0   \n",
       "8123              0              1              0            0            0   \n",
       "\n",
       "      ...  population_n  population_s  population_v  population_y  habitat_g  \\\n",
       "0     ...             0             1             0             0          0   \n",
       "1     ...             1             0             0             0          1   \n",
       "2     ...             1             0             0             0          0   \n",
       "3     ...             0             1             0             0          0   \n",
       "4     ...             0             0             0             0          1   \n",
       "...   ...           ...           ...           ...           ...        ...   \n",
       "8119  ...             0             0             0             0          0   \n",
       "8120  ...             0             0             1             0          0   \n",
       "8121  ...             0             0             0             0          0   \n",
       "8122  ...             0             0             1             0          0   \n",
       "8123  ...             0             0             0             0          0   \n",
       "\n",
       "      habitat_l  habitat_m  habitat_p  habitat_u  habitat_w  \n",
       "0             0          0          0          1          0  \n",
       "1             0          0          0          0          0  \n",
       "2             0          1          0          0          0  \n",
       "3             0          0          0          1          0  \n",
       "4             0          0          0          0          0  \n",
       "...         ...        ...        ...        ...        ...  \n",
       "8119          1          0          0          0          0  \n",
       "8120          1          0          0          0          0  \n",
       "8121          1          0          0          0          0  \n",
       "8122          1          0          0          0          0  \n",
       "8123          1          0          0          0          0  \n",
       "\n",
       "[8124 rows x 95 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = df.drop(['class'],axis= 1)\n",
    "X = pd.get_dummies(X,drop_first=True)\n",
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0871549e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       p\n",
       "1       e\n",
       "2       e\n",
       "3       p\n",
       "4       e\n",
       "       ..\n",
       "8119    e\n",
       "8120    e\n",
       "8121    e\n",
       "8122    p\n",
       "8123    e\n",
       "Name: class, Length: 8124, dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y= df['class']\n",
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "b907fe3a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='class', ylabel='count'>"
      ]
     },
     "execution_count": 10,
     "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": [
    "sns.countplot(data=df, x= 'class')  # Pretty well Balanced Dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9a3e7eb6",
   "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",
       "      <th>unique</th>\n",
       "      <th>top</th>\n",
       "      <th>freq</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>class</th>\n",
       "      <td>8124</td>\n",
       "      <td>2</td>\n",
       "      <td>e</td>\n",
       "      <td>4208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cap-shape</th>\n",
       "      <td>8124</td>\n",
       "      <td>6</td>\n",
       "      <td>x</td>\n",
       "      <td>3656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cap-surface</th>\n",
       "      <td>8124</td>\n",
       "      <td>4</td>\n",
       "      <td>y</td>\n",
       "      <td>3244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cap-color</th>\n",
       "      <td>8124</td>\n",
       "      <td>10</td>\n",
       "      <td>n</td>\n",
       "      <td>2284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bruises</th>\n",
       "      <td>8124</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>4748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>odor</th>\n",
       "      <td>8124</td>\n",
       "      <td>9</td>\n",
       "      <td>n</td>\n",
       "      <td>3528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gill-attachment</th>\n",
       "      <td>8124</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>7914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gill-spacing</th>\n",
       "      <td>8124</td>\n",
       "      <td>2</td>\n",
       "      <td>c</td>\n",
       "      <td>6812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gill-size</th>\n",
       "      <td>8124</td>\n",
       "      <td>2</td>\n",
       "      <td>b</td>\n",
       "      <td>5612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gill-color</th>\n",
       "      <td>8124</td>\n",
       "      <td>12</td>\n",
       "      <td>b</td>\n",
       "      <td>1728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-shape</th>\n",
       "      <td>8124</td>\n",
       "      <td>2</td>\n",
       "      <td>t</td>\n",
       "      <td>4608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-root</th>\n",
       "      <td>8124</td>\n",
       "      <td>5</td>\n",
       "      <td>b</td>\n",
       "      <td>3776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-surface-above-ring</th>\n",
       "      <td>8124</td>\n",
       "      <td>4</td>\n",
       "      <td>s</td>\n",
       "      <td>5176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-surface-below-ring</th>\n",
       "      <td>8124</td>\n",
       "      <td>4</td>\n",
       "      <td>s</td>\n",
       "      <td>4936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-color-above-ring</th>\n",
       "      <td>8124</td>\n",
       "      <td>9</td>\n",
       "      <td>w</td>\n",
       "      <td>4464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-color-below-ring</th>\n",
       "      <td>8124</td>\n",
       "      <td>9</td>\n",
       "      <td>w</td>\n",
       "      <td>4384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>veil-type</th>\n",
       "      <td>8124</td>\n",
       "      <td>1</td>\n",
       "      <td>p</td>\n",
       "      <td>8124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>veil-color</th>\n",
       "      <td>8124</td>\n",
       "      <td>4</td>\n",
       "      <td>w</td>\n",
       "      <td>7924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ring-number</th>\n",
       "      <td>8124</td>\n",
       "      <td>3</td>\n",
       "      <td>o</td>\n",
       "      <td>7488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ring-type</th>\n",
       "      <td>8124</td>\n",
       "      <td>5</td>\n",
       "      <td>p</td>\n",
       "      <td>3968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>spore-print-color</th>\n",
       "      <td>8124</td>\n",
       "      <td>9</td>\n",
       "      <td>w</td>\n",
       "      <td>2388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>population</th>\n",
       "      <td>8124</td>\n",
       "      <td>6</td>\n",
       "      <td>v</td>\n",
       "      <td>4040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>habitat</th>\n",
       "      <td>8124</td>\n",
       "      <td>7</td>\n",
       "      <td>d</td>\n",
       "      <td>3148</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         count unique top  freq\n",
       "class                     8124      2   e  4208\n",
       "cap-shape                 8124      6   x  3656\n",
       "cap-surface               8124      4   y  3244\n",
       "cap-color                 8124     10   n  2284\n",
       "bruises                   8124      2   f  4748\n",
       "odor                      8124      9   n  3528\n",
       "gill-attachment           8124      2   f  7914\n",
       "gill-spacing              8124      2   c  6812\n",
       "gill-size                 8124      2   b  5612\n",
       "gill-color                8124     12   b  1728\n",
       "stalk-shape               8124      2   t  4608\n",
       "stalk-root                8124      5   b  3776\n",
       "stalk-surface-above-ring  8124      4   s  5176\n",
       "stalk-surface-below-ring  8124      4   s  4936\n",
       "stalk-color-above-ring    8124      9   w  4464\n",
       "stalk-color-below-ring    8124      9   w  4384\n",
       "veil-type                 8124      1   p  8124\n",
       "veil-color                8124      4   w  7924\n",
       "ring-number               8124      3   o  7488\n",
       "ring-type                 8124      5   p  3968\n",
       "spore-print-color         8124      9   w  2388\n",
       "population                8124      6   v  4040\n",
       "habitat                   8124      7   d  3148"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe().transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "56910b1e",
   "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>index</th>\n",
       "      <th>count</th>\n",
       "      <th>unique</th>\n",
       "      <th>top</th>\n",
       "      <th>freq</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>veil-type</td>\n",
       "      <td>8124</td>\n",
       "      <td>1</td>\n",
       "      <td>p</td>\n",
       "      <td>8124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>class</td>\n",
       "      <td>8124</td>\n",
       "      <td>2</td>\n",
       "      <td>e</td>\n",
       "      <td>4208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>bruises</td>\n",
       "      <td>8124</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>4748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>gill-attachment</td>\n",
       "      <td>8124</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>7914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>gill-spacing</td>\n",
       "      <td>8124</td>\n",
       "      <td>2</td>\n",
       "      <td>c</td>\n",
       "      <td>6812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>gill-size</td>\n",
       "      <td>8124</td>\n",
       "      <td>2</td>\n",
       "      <td>b</td>\n",
       "      <td>5612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>stalk-shape</td>\n",
       "      <td>8124</td>\n",
       "      <td>2</td>\n",
       "      <td>t</td>\n",
       "      <td>4608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>ring-number</td>\n",
       "      <td>8124</td>\n",
       "      <td>3</td>\n",
       "      <td>o</td>\n",
       "      <td>7488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>cap-surface</td>\n",
       "      <td>8124</td>\n",
       "      <td>4</td>\n",
       "      <td>y</td>\n",
       "      <td>3244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>veil-color</td>\n",
       "      <td>8124</td>\n",
       "      <td>4</td>\n",
       "      <td>w</td>\n",
       "      <td>7924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>stalk-surface-below-ring</td>\n",
       "      <td>8124</td>\n",
       "      <td>4</td>\n",
       "      <td>s</td>\n",
       "      <td>4936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>stalk-surface-above-ring</td>\n",
       "      <td>8124</td>\n",
       "      <td>4</td>\n",
       "      <td>s</td>\n",
       "      <td>5176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>ring-type</td>\n",
       "      <td>8124</td>\n",
       "      <td>5</td>\n",
       "      <td>p</td>\n",
       "      <td>3968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>stalk-root</td>\n",
       "      <td>8124</td>\n",
       "      <td>5</td>\n",
       "      <td>b</td>\n",
       "      <td>3776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>cap-shape</td>\n",
       "      <td>8124</td>\n",
       "      <td>6</td>\n",
       "      <td>x</td>\n",
       "      <td>3656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>population</td>\n",
       "      <td>8124</td>\n",
       "      <td>6</td>\n",
       "      <td>v</td>\n",
       "      <td>4040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>habitat</td>\n",
       "      <td>8124</td>\n",
       "      <td>7</td>\n",
       "      <td>d</td>\n",
       "      <td>3148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>stalk-color-above-ring</td>\n",
       "      <td>8124</td>\n",
       "      <td>9</td>\n",
       "      <td>w</td>\n",
       "      <td>4464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>stalk-color-below-ring</td>\n",
       "      <td>8124</td>\n",
       "      <td>9</td>\n",
       "      <td>w</td>\n",
       "      <td>4384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>odor</td>\n",
       "      <td>8124</td>\n",
       "      <td>9</td>\n",
       "      <td>n</td>\n",
       "      <td>3528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>spore-print-color</td>\n",
       "      <td>8124</td>\n",
       "      <td>9</td>\n",
       "      <td>w</td>\n",
       "      <td>2388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>cap-color</td>\n",
       "      <td>8124</td>\n",
       "      <td>10</td>\n",
       "      <td>n</td>\n",
       "      <td>2284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>gill-color</td>\n",
       "      <td>8124</td>\n",
       "      <td>12</td>\n",
       "      <td>b</td>\n",
       "      <td>1728</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       index count unique top  freq\n",
       "16                 veil-type  8124      1   p  8124\n",
       "0                      class  8124      2   e  4208\n",
       "4                    bruises  8124      2   f  4748\n",
       "6            gill-attachment  8124      2   f  7914\n",
       "7               gill-spacing  8124      2   c  6812\n",
       "8                  gill-size  8124      2   b  5612\n",
       "10               stalk-shape  8124      2   t  4608\n",
       "18               ring-number  8124      3   o  7488\n",
       "2                cap-surface  8124      4   y  3244\n",
       "17                veil-color  8124      4   w  7924\n",
       "13  stalk-surface-below-ring  8124      4   s  4936\n",
       "12  stalk-surface-above-ring  8124      4   s  5176\n",
       "19                 ring-type  8124      5   p  3968\n",
       "11                stalk-root  8124      5   b  3776\n",
       "1                  cap-shape  8124      6   x  3656\n",
       "21                population  8124      6   v  4040\n",
       "22                   habitat  8124      7   d  3148\n",
       "14    stalk-color-above-ring  8124      9   w  4464\n",
       "15    stalk-color-below-ring  8124      9   w  4384\n",
       "5                       odor  8124      9   n  3528\n",
       "20         spore-print-color  8124      9   w  2388\n",
       "3                  cap-color  8124     10   n  2284\n",
       "9                 gill-color  8124     12   b  1728"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_describe = df.describe().transpose().reset_index().sort_values('unique')\n",
    "data_describe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "152d0bea",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 2400x1200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6),dpi=200)\n",
    "sns.barplot(data=data_describe, x='index', y='unique')\n",
    "plt.xticks(rotation=90);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "966c9c3c",
   "metadata": {},
   "source": [
    "# Train | Test Split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "e810aaed",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import classification_report, plot_confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0e138348",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=101)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88fba2bb",
   "metadata": {},
   "source": [
    "# <<<<<<M.L Models>>>>>>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c38e5574",
   "metadata": {},
   "outputs": [],
   "source": [
    "def report_model(model):\n",
    "    model.fit(X_train,y_train)\n",
    "    y_pred = model.predict(X_test)\n",
    "    print(classification_report(y_test,y_pred))\n",
    "    plot_confusion_matrix(model,X_test,y_test)\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc33dfca",
   "metadata": {},
   "source": [
    "## Ada Boost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2fd22378",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import AdaBoostClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "13bb39fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "ada_model = AdaBoostClassifier(n_estimators=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ab181552",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           e       0.95      0.80      0.87       851\n",
      "           p       0.81      0.96      0.88       774\n",
      "\n",
      "    accuracy                           0.88      1625\n",
      "   macro avg       0.88      0.88      0.87      1625\n",
      "weighted avg       0.89      0.88      0.87      1625\n",
      "\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": [
    "report_model(ada_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b5c63ce",
   "metadata": {},
   "source": [
    "# Evaluate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "87450875",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "accuracy_error = []\n",
    "for n in range(1,100):\n",
    "    model=AdaBoostClassifier(n_estimators=n)\n",
    "    model.fit(X_train,y_train)\n",
    "    y_pred = model.predict(X_test)\n",
    "    error = 1 - accuracy_score(y_test, y_pred)\n",
    "    accuracy_error.append(error)\n",
    "    \n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "a7265836",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2cc7eb20070>]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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zS0nh7nVzQl+2xHLPgaP0LKiFfUdrqXa/G6+6MbOEFDboe7vb2b3/CLv3H+G8hW1A7QlUC9tbPaM3s6QUNuj7FnUwOh48M3SAxZ3Vie1dHRXX6M0sKcUN+mzlzaFjoyzubJvY3tXu+92YWVoKG/QnblcMsHjhydddHZV3PH3KzGy+K2zQL+1qR9kdehYvrC/dtHLAF0yZWUIKG/St5RaWZCWb8yaXbrzqxswSUtigh5NXyL6jRt9R4fDxMY6N+g6WZpaGYgd9ds+bxQtPBv3C7EpZ38HSzFJR2CtjAT598bkcPDJCR+vJ34au9uxWxYdHOPestqkONTObNwod9Nd+dCnXfnTpO7aduCe96/RmlopCl24a6c5KN2++7ZU3ZpYGB/0kC9s9ozeztDjoJ5l4nKAvmjKzRDjoJ1lQLVNqEft9vxszS4SDfhJJvt+NmSXFQd/Awg5fHWtm6XDQN9DVXnGN3syS4aBvoLujlTd9YzMzS4SDvoGFHa7Rm1k6HPQNdLW3+l43ZpaMXEEvaY2kHZIGJd3WYL8k3ZHtf1rSZdn2Pkk/lrRd0jZJt8z2AOZCV0eFt46NMjI23uyumJmdtmmDXlIJuBNYC/QD10nqn9RsLbAy+9kA3JVtHwW+GhGXAFcANzU49n1n4qIpz+rNLAF5ZvSrgcGI2BkRx4H7gXWT2qwD7o2ax4AuSUsiYk9EPAkQEYeA7cCyWez/nOjK7neze/+RJvfEzOz05Qn6ZcCuuvdDvDusp20jaTlwKfB4oy+RtEHSgKSB4eHhHN2aOx//rbPpaC2x6ac7m9oPM7PZkCfo1WBbzKSNpAXAg8CtEXGw0ZdExKaIWBURq3p6enJ0a+6cs6DKlz+xgoef3sOzrxxoal/MzE5XnqAfAvrq3vcCu/O2kVShFvL3RcRDp97VM+uPPnkhXR0V/uLRHc3uipnZackT9FuBlZJWSGoF1gObJ7XZDFyfrb65AjgQEXskCfgOsD0ibp/Vns+xzrYKN33qIn7662F+9sJrze6OmdkpmzboI2IUuBl4lNrJ1L+LiG2SbpR0Y9ZsC7ATGAT+F/Dvs+1XAV8CPi3pqeznmtkexFz50pUXsGRhG3/xyA4iJlerzMzmh1yPEoyILdTCvH7bxrrXAdzU4Lh/pHH9fl5oq5S45eqV3PbQMzz+4htcceHZze6SmdmM+crYaaz58GIA/nnX/uZ2xMzsFDnop9HV0cqyrnae29NwsZCZ2fuegz6HS5Z08txuB72ZzU8O+hz6l3bywvBbHB0Za3ZXzMxmzEGfQ/+STsYDduw91OyumJnNmIM+hw8t7QRwnd7M5iUHfQ693e2cVS27Tm9m85KDPgdJXLK00zN6M5uXHPQ59S/pZPueg4yN+wpZM5tfHPQ59S/t5PDxMV56/e1md8XMbEYc9Dn1L/EJWTObnxz0Oa08bwHlFvmErJnNOw76nKrlEhedu8AzejObdxz0M9C/NN+tEH42+BpPvvzmGeiRmdn0HPQz0L+kk32HjjF86NiUbY6OjPHv7nuSW+9/inGv0DGz9wEH/Qz057hC9pFn93LgyAgvv3GYn73w+pnqmpnZlBz0M/CRZQvpaC3x9wO7pmzzt4+/zPmLOujuqPC3v3jpDPbOzKwxB/0MnNVW4cufWMHDT+/h2VcOvGv/4L5D/OI3b/CFy8/nDy7r5fvbXn3PMo+Z2ZngoJ+hP/rkhXR1VPjzR371rn3f+8UuKiXxL3+3l/Wrz2d0PHjgiaEm9NLM7CQH/Qx1tlW46VMX8f+ef42fDb42sf3oyBgPPjnEv+hfzDkLqlx07gJWr1jE/Vtf9klZM2sqB/0p+NKVF7BkYRt//ugOas9Fh0e37WX/4RG+cPn5E+3+zeXn89Lrh/n5Tp+UNbPmKTe7A/NRW6XErZ9ZyX968Bn+1caf01Yp8fy+Q1xwdgdXXnj2RLvPfWgxXR0V/uePBvnwsoUsbK80sddmVlSe0Z+iP7isl3UfW0oAR0bG6O3u4D9+7oO0tGiiTVulxH/47G/z+Iuv85nb/4GHn9498S8AM7MzRXmCR9Ia4NtACbg7Iv77pP3K9l8DHAb+bUQ8mefYRlatWhUDAwMzHMr717OvHOAbDz3DM68c4LfPW0BH67v/IdXZXuGWqy/idy9Y1IQemtl8J+mJiFjVcN90QS+pBPwa+CwwBGwFrouI5+raXAP8MbWgvxz4dkRcnufYRlILeoDRsXH++rGX+MmOYRr9ju/Ye5B9h47xhdXn8/U1F7vMY2Yz8l5Bn6dGvxoYjIid2YfdD6wD6sN6HXBv1P7WeExSl6QlwPIcxxZCudTCDVet4IarVjTc/9axUf7HD37Nd//pRR5+eg/nnlU9wz00s2br7mjl7268ctY/N0/QLwPqLwUdojZrn67NspzHAiBpA7AB4Pzzz2/UJGkLqmX+y7X9fP5jy/juP73I0dGxZnfJzM6wzra5+Zd8nqBXg22Tqw9TtclzbG1jxCZgE9RKNzn6laSP9C7k9n/9sWZ3w8wSkifoh4C+uve9wO6cbVpzHGtmZnMoz/LKrcBKSSsktQLrgc2T2mwGrlfNFcCBiNiT81gzM5tD087oI2JU0s3Ao9SWSN4TEdsk3Zjt3whsobbiZpDa8sob3uvYORmJmZk1lGsd/ZmW4vJKM7O59F7LK31lrJlZ4hz0ZmaJc9CbmSXOQW9mlrj35clYScPATB64eg7w2rSt0uNxF4vHXSwzHfcFEdHTaMf7MuhnStLAVGebU+ZxF4vHXSyzOW6XbszMEuegNzNLXCpBv6nZHWgSj7tYPO5imbVxJ1GjNzOzqaUyozczsyk46M3MEjevg17SGkk7JA1Kuq3Z/Zkrkvok/VjSdknbJN2SbV8k6QeSns9+7W52X+eCpJKkX0p6OHuf/Lizx3E+IOlX2Z/7lQUZ959k/40/K+l7ktpSHbekeyTtk/Rs3bYpxyrpG1nW7ZD0uZl817wN+uzB43cCa4F+4DpJ/c3t1ZwZBb4aEZcAVwA3ZWO9DfhhRKwEfpi9T9EtwPa690UY97eBRyLiYuB3qI0/6XFLWgZ8BVgVER+mdmvz9aQ77v8NrJm0reFYs//f1wMfyo75yywDc5m3QU/dQ8sj4jhw4sHjyYmIPRHxZPb6ELX/6ZdRG+9fZc3+Cvh8Uzo4hyT1Ar8H3F23OelxS+oEPgl8ByAijkfEfhIfd6YMtEsqAx3UnkiX5Lgj4qfAG5M2TzXWdcD9EXEsIl6k9uyP1Xm/az4H/VQPJE+apOXApcDjwHnZk7zIfj23iV2bK98Cvg6M121LfdwXAsPAd7OS1d2SPkDi446IV4BvAi8De6g9qe77JD7uSaYa62nl3XwO+twPHk+FpAXAg8CtEXGw2f2Za5KuBfZFxBPN7ssZVgYuA+6KiEuBt0mnXDGlrB69DlgBLAU+IOmLze3V+8Zp5d18Dvo8Dy1PhqQKtZC/LyIeyja/KmlJtn8JsK9Z/ZsjVwG/L+k31Epzn5b0N6Q/7iFgKCIez94/QC34Ux/3Z4AXI2I4IkaAh4CPk/6460011tPKu/kc9IV58LgkUavXbo+I2+t2bQb+MHv9h8D/PdN9m0sR8Y2I6I2I5dT+fH8UEV8k/XHvBXZJ+mC26WrgORIfN7WSzRWSOrL/5q+mdj4q9XHXm2qsm4H1kqqSVgArgV/k/tSImLc/1B5I/mvgBeBPm92fORznJ6j9M+1p4Kns5xrgbGpn5p/Pfl3U7L7O4e/Bp4CHs9fJjxv4GDCQ/Zn/H6C7IOP+r8CvgGeBvwaqqY4b+B61cxEj1GbsX36vsQJ/mmXdDmDtTL7Lt0AwM0vcfC7dmJlZDg56M7PEOejNzBLnoDczS5yD3swscQ56M7PEOejNzBL3/wGPx7NKfVgxGwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(range(1,100), accuracy_error) # Looks like n_estimators around 20 is Sweet spot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "b08db4d8",
   "metadata": {},
   "outputs": [],
   "source": [
    "ada_model = AdaBoostClassifier(n_estimators=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "1537b32c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           e       1.00      1.00      1.00       851\n",
      "           p       1.00      1.00      1.00       774\n",
      "\n",
      "    accuracy                           1.00      1625\n",
      "   macro avg       1.00      1.00      1.00      1625\n",
      "weighted avg       1.00      1.00      1.00      1625\n",
      "\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": [
    "report_model(ada_model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "54dcedb8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  ,\n",
       "       0.  , 0.  , 0.  , 0.  , 0.05, 0.  , 0.05, 0.05, 0.05, 0.  , 0.  ,\n",
       "       0.1 , 0.05, 0.  , 0.  , 0.  , 0.05, 0.15, 0.  , 0.  , 0.  , 0.  ,\n",
       "       0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  ,\n",
       "       0.  , 0.05, 0.  , 0.  , 0.  , 0.  , 0.05, 0.  , 0.  , 0.  , 0.  ,\n",
       "       0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.05, 0.  , 0.  , 0.  ,\n",
       "       0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  ,\n",
       "       0.  , 0.  , 0.  , 0.05, 0.  , 0.1 , 0.  , 0.05, 0.  , 0.  , 0.1 ,\n",
       "       0.  , 0.  , 0.  , 0.  , 0.  , 0.  , 0.  ])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features = ada_model.feature_importances_\n",
    "features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "51e57ece",
   "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>Important Features</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>stalk-surface-above-ring_k</th>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>odor_p</th>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gill-spacing_w</th>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-surface-below-ring_y</th>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>odor_f</th>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>odor_c</th>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bruises_t</th>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>spore-print-color_r</th>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cap-color_w</th>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>population_c</th>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-color-below-ring_n</th>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>spore-print-color_w</th>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>population_v</th>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>odor_n</th>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gill-size_n</th>\n",
       "      <td>0.15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Important Features\n",
       "stalk-surface-above-ring_k                0.05\n",
       "odor_p                                    0.05\n",
       "gill-spacing_w                            0.05\n",
       "stalk-surface-below-ring_y                0.05\n",
       "odor_f                                    0.05\n",
       "odor_c                                    0.05\n",
       "bruises_t                                 0.05\n",
       "spore-print-color_r                       0.05\n",
       "cap-color_w                               0.05\n",
       "population_c                              0.05\n",
       "stalk-color-below-ring_n                  0.05\n",
       "spore-print-color_w                       0.10\n",
       "population_v                              0.10\n",
       "odor_n                                    0.10\n",
       "gill-size_n                               0.15"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_features = pd.DataFrame(index = X.columns, data= features, columns=['Important Features']).sort_values('Important Features')\n",
    "imp_features = imp_features[imp_features['Important Features']>0]\n",
    "imp_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "e8d03ac5",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 2400x1200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6),dpi=200)\n",
    "sns.barplot(x=imp_features.index, y=imp_features['Important Features'])\n",
    "plt.xticks(rotation=90);\n",
    "# From Barplot , we can see that gill-size_n is most Importance feature in this model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "5f9e5c4e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='habitat', ylabel='count'>"
      ]
     },
     "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": [
    "sns.countplot(data=df, x='habitat',hue='class')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0882b8ec",
   "metadata": {},
   "source": [
    "## Gradient Boosting and Grid Search with CV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e3a664e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import GradientBoostingClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "2b5a960a",
   "metadata": {},
   "outputs": [],
   "source": [
    "gbc_model = GradientBoostingClassifier()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "13df1c13",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "f527f717",
   "metadata": {},
   "outputs": [],
   "source": [
    "parameters = {'learning_rate':[0.05,0.1,0.2,0.5],\n",
    "              'n_estimators':[50,100,150]\n",
    "             }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "a32965cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "grid_model = GridSearchCV(gbc_model,param_grid=parameters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "cf8ad34e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GridSearchCV(estimator=GradientBoostingClassifier(),\n",
       "             param_grid={'learning_rate': [0.05, 0.1, 0.2, 0.5],\n",
       "                         'n_estimators': [50, 100, 150]})"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid_model.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "e5cb955e",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = model.predict(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e66f976d",
   "metadata": {},
   "source": [
    "## Performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "1d0f4c2b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           e       1.00      1.00      1.00       851\n",
      "           p       1.00      1.00      1.00       774\n",
      "\n",
      "    accuracy                           1.00      1625\n",
      "   macro avg       1.00      1.00      1.00      1625\n",
      "weighted avg       1.00      1.00      1.00      1625\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test,y_pred))\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "f88e4a39",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<sklearn.metrics._plot.confusion_matrix.ConfusionMatrixDisplay at 0x2cc31110f40>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "plot_confusion_matrix(model,X_test,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "401af010",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'learning_rate': 0.1, 'n_estimators': 150}"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid_model.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "495ef495",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3.34036532e-04, 5.61048428e-17, 6.23961796e-18, 3.91764711e-07,\n",
       "       1.12324468e-21, 1.27308767e-03, 5.18881533e-16, 9.86761091e-19,\n",
       "       5.21146462e-06, 1.85018368e-18, 0.00000000e+00, 0.00000000e+00,\n",
       "       4.52515500e-19, 4.32684958e-17, 0.00000000e+00, 6.50778488e-10,\n",
       "       2.42654229e-03, 5.41684228e-02, 7.59870697e-04, 2.17587813e-02,\n",
       "       1.98378399e-02, 9.91160706e-05, 6.18812038e-01, 3.95930597e-03,\n",
       "       0.00000000e+00, 0.00000000e+00, 2.34012429e-18, 1.28019299e-02,\n",
       "       1.08122288e-02, 0.00000000e+00, 1.53102805e-16, 6.52971477e-17,\n",
       "       0.00000000e+00, 1.93412001e-17, 0.00000000e+00, 7.04264929e-17,\n",
       "       8.11232269e-23, 2.24648936e-21, 6.21161133e-18, 8.78221334e-19,\n",
       "       1.17489218e-07, 2.01549995e-05, 1.32150154e-01, 4.67676940e-03,\n",
       "       4.85502691e-02, 5.15339463e-04, 2.45624000e-05, 7.63905743e-05,\n",
       "       1.15326277e-16, 1.19874844e-06, 1.88625199e-02, 3.13408769e-03,\n",
       "       0.00000000e+00, 0.00000000e+00, 5.17953908e-04, 0.00000000e+00,\n",
       "       0.00000000e+00, 2.15522752e-03, 0.00000000e+00, 9.46539844e-07,\n",
       "       0.00000000e+00, 0.00000000e+00, 5.16061245e-05, 0.00000000e+00,\n",
       "       0.00000000e+00, 1.14195443e-03, 2.53781392e-03, 0.00000000e+00,\n",
       "       1.56265710e-08, 0.00000000e+00, 3.45180866e-04, 6.45293734e-04,\n",
       "       1.03354387e-04, 0.00000000e+00, 2.73852571e-04, 5.68962760e-04,\n",
       "       2.47657355e-04, 2.63645747e-04, 2.69501132e-04, 0.00000000e+00,\n",
       "       2.83661014e-02, 4.68504894e-03, 5.07479392e-04, 0.00000000e+00,\n",
       "       1.30072613e-03, 0.00000000e+00, 1.85397274e-07, 9.50473473e-04,\n",
       "       6.27430991e-08, 4.43225526e-19, 0.00000000e+00, 0.00000000e+00,\n",
       "       0.00000000e+00, 6.58842184e-06, 0.00000000e+00])"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features = grid_model.best_estimator_.feature_importances_\n",
    "features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "2786285d",
   "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>Important Features</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>stalk-color-below-ring_w</th>\n",
       "      <td>0.001142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cap-surface_g</th>\n",
       "      <td>0.001273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>population_c</th>\n",
       "      <td>0.001301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-color-above-ring_w</th>\n",
       "      <td>0.002155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cap-color_y</th>\n",
       "      <td>0.002427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-color-below-ring_y</th>\n",
       "      <td>0.002538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-color-above-ring_c</th>\n",
       "      <td>0.003134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>odor_p</th>\n",
       "      <td>0.003959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-root_e</th>\n",
       "      <td>0.004677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>spore-print-color_u</th>\n",
       "      <td>0.004685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gill-size_n</th>\n",
       "      <td>0.010812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gill-spacing_w</th>\n",
       "      <td>0.012802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-surface-below-ring_y</th>\n",
       "      <td>0.018863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>odor_l</th>\n",
       "      <td>0.019838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>odor_f</th>\n",
       "      <td>0.021759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>spore-print-color_r</th>\n",
       "      <td>0.028366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-root_r</th>\n",
       "      <td>0.048550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bruises_t</th>\n",
       "      <td>0.054168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>stalk-root_c</th>\n",
       "      <td>0.132150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>odor_n</th>\n",
       "      <td>0.618812</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Important Features\n",
       "stalk-color-below-ring_w              0.001142\n",
       "cap-surface_g                         0.001273\n",
       "population_c                          0.001301\n",
       "stalk-color-above-ring_w              0.002155\n",
       "cap-color_y                           0.002427\n",
       "stalk-color-below-ring_y              0.002538\n",
       "stalk-color-above-ring_c              0.003134\n",
       "odor_p                                0.003959\n",
       "stalk-root_e                          0.004677\n",
       "spore-print-color_u                   0.004685\n",
       "gill-size_n                           0.010812\n",
       "gill-spacing_w                        0.012802\n",
       "stalk-surface-below-ring_y            0.018863\n",
       "odor_l                                0.019838\n",
       "odor_f                                0.021759\n",
       "spore-print-color_r                   0.028366\n",
       "stalk-root_r                          0.048550\n",
       "bruises_t                             0.054168\n",
       "stalk-root_c                          0.132150\n",
       "odor_n                                0.618812"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_features = pd.DataFrame(index = X.columns, data= features, columns=['Important Features']).sort_values('Important Features')\n",
    "imp_features = imp_features[imp_features['Important Features']>0.001]\n",
    "imp_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "961c18dc",
   "metadata": {},
   "outputs": [
    {
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\n",
      "text/plain": [
       "<Figure size 2400x1200 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6),dpi=200)\n",
    "sns.barplot(x=imp_features.index, y=imp_features['Important Features'])\n",
    "plt.xticks(rotation=90);\n",
    "# odor_n is most Important Feature in this model"
   ]
  }
 ],
 "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}