Part 4: Feature_Selection_Selectkbest_ExtraTreeReg_corr_infogain.ipynb

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      "cell_type": "markdown",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/gulabpatel/Feature_Selection_Methods/blob/main/Part%204%3A%20Feature_Selection_Selectkbest_ExtraTreeReg_corr_infogain.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eRp32CP2tEKw"
      },
      "source": [
        "### Feature Selection Techniques"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "difZHjVytEKz",
        "outputId": "51eb6e34-6fef-47f8-d200-66151bd8e500"
      },
      "source": [
        "import pandas as pd\n",
        "df=pd.read_csv('mobile_dataset.csv')\n",
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>battery_power</th>\n",
              "      <th>blue</th>\n",
              "      <th>clock_speed</th>\n",
              "      <th>dual_sim</th>\n",
              "      <th>fc</th>\n",
              "      <th>four_g</th>\n",
              "      <th>int_memory</th>\n",
              "      <th>m_dep</th>\n",
              "      <th>mobile_wt</th>\n",
              "      <th>n_cores</th>\n",
              "      <th>...</th>\n",
              "      <th>px_height</th>\n",
              "      <th>px_width</th>\n",
              "      <th>ram</th>\n",
              "      <th>sc_h</th>\n",
              "      <th>sc_w</th>\n",
              "      <th>talk_time</th>\n",
              "      <th>three_g</th>\n",
              "      <th>touch_screen</th>\n",
              "      <th>wifi</th>\n",
              "      <th>price_range</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>842</td>\n",
              "      <td>0</td>\n",
              "      <td>2.2</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>0.6</td>\n",
              "      <td>188</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>20</td>\n",
              "      <td>756</td>\n",
              "      <td>2549</td>\n",
              "      <td>9</td>\n",
              "      <td>7</td>\n",
              "      <td>19</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1021</td>\n",
              "      <td>1</td>\n",
              "      <td>0.5</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>53</td>\n",
              "      <td>0.7</td>\n",
              "      <td>136</td>\n",
              "      <td>3</td>\n",
              "      <td>...</td>\n",
              "      <td>905</td>\n",
              "      <td>1988</td>\n",
              "      <td>2631</td>\n",
              "      <td>17</td>\n",
              "      <td>3</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>563</td>\n",
              "      <td>1</td>\n",
              "      <td>0.5</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>41</td>\n",
              "      <td>0.9</td>\n",
              "      <td>145</td>\n",
              "      <td>5</td>\n",
              "      <td>...</td>\n",
              "      <td>1263</td>\n",
              "      <td>1716</td>\n",
              "      <td>2603</td>\n",
              "      <td>11</td>\n",
              "      <td>2</td>\n",
              "      <td>9</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>615</td>\n",
              "      <td>1</td>\n",
              "      <td>2.5</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>0.8</td>\n",
              "      <td>131</td>\n",
              "      <td>6</td>\n",
              "      <td>...</td>\n",
              "      <td>1216</td>\n",
              "      <td>1786</td>\n",
              "      <td>2769</td>\n",
              "      <td>16</td>\n",
              "      <td>8</td>\n",
              "      <td>11</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1821</td>\n",
              "      <td>1</td>\n",
              "      <td>1.2</td>\n",
              "      <td>0</td>\n",
              "      <td>13</td>\n",
              "      <td>1</td>\n",
              "      <td>44</td>\n",
              "      <td>0.6</td>\n",
              "      <td>141</td>\n",
              "      <td>2</td>\n",
              "      <td>...</td>\n",
              "      <td>1208</td>\n",
              "      <td>1212</td>\n",
              "      <td>1411</td>\n",
              "      <td>8</td>\n",
              "      <td>2</td>\n",
              "      <td>15</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 21 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "   battery_power  blue  clock_speed  dual_sim  fc  four_g  int_memory  m_dep  \\\n",
              "0            842     0          2.2         0   1       0           7    0.6   \n",
              "1           1021     1          0.5         1   0       1          53    0.7   \n",
              "2            563     1          0.5         1   2       1          41    0.9   \n",
              "3            615     1          2.5         0   0       0          10    0.8   \n",
              "4           1821     1          1.2         0  13       1          44    0.6   \n",
              "\n",
              "   mobile_wt  n_cores  ...  px_height  px_width   ram  sc_h  sc_w  talk_time  \\\n",
              "0        188        2  ...         20       756  2549     9     7         19   \n",
              "1        136        3  ...        905      1988  2631    17     3          7   \n",
              "2        145        5  ...       1263      1716  2603    11     2          9   \n",
              "3        131        6  ...       1216      1786  2769    16     8         11   \n",
              "4        141        2  ...       1208      1212  1411     8     2         15   \n",
              "\n",
              "   three_g  touch_screen  wifi  price_range  \n",
              "0        0             0     1            1  \n",
              "1        1             1     0            2  \n",
              "2        1             1     0            2  \n",
              "3        1             0     0            2  \n",
              "4        1             1     0            1  \n",
              "\n",
              "[5 rows x 21 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NYkxPCP-tEK0"
      },
      "source": [
        "#### Univariate Selection"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kB-UE-O-tEK1"
      },
      "source": [
        "X=df.iloc[:,:-1]\n",
        "y=df['price_range']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mz6BFlhktEK1",
        "outputId": "4a803ee2-666d-4443-afe4-c28627381f66"
      },
      "source": [
        "X.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "\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>battery_power</th>\n",
              "      <th>blue</th>\n",
              "      <th>clock_speed</th>\n",
              "      <th>dual_sim</th>\n",
              "      <th>fc</th>\n",
              "      <th>four_g</th>\n",
              "      <th>int_memory</th>\n",
              "      <th>m_dep</th>\n",
              "      <th>mobile_wt</th>\n",
              "      <th>n_cores</th>\n",
              "      <th>pc</th>\n",
              "      <th>px_height</th>\n",
              "      <th>px_width</th>\n",
              "      <th>ram</th>\n",
              "      <th>sc_h</th>\n",
              "      <th>sc_w</th>\n",
              "      <th>talk_time</th>\n",
              "      <th>three_g</th>\n",
              "      <th>touch_screen</th>\n",
              "      <th>wifi</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>842</td>\n",
              "      <td>0</td>\n",
              "      <td>2.2</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>0.6</td>\n",
              "      <td>188</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>20</td>\n",
              "      <td>756</td>\n",
              "      <td>2549</td>\n",
              "      <td>9</td>\n",
              "      <td>7</td>\n",
              "      <td>19</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1021</td>\n",
              "      <td>1</td>\n",
              "      <td>0.5</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>53</td>\n",
              "      <td>0.7</td>\n",
              "      <td>136</td>\n",
              "      <td>3</td>\n",
              "      <td>6</td>\n",
              "      <td>905</td>\n",
              "      <td>1988</td>\n",
              "      <td>2631</td>\n",
              "      <td>17</td>\n",
              "      <td>3</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>563</td>\n",
              "      <td>1</td>\n",
              "      <td>0.5</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>41</td>\n",
              "      <td>0.9</td>\n",
              "      <td>145</td>\n",
              "      <td>5</td>\n",
              "      <td>6</td>\n",
              "      <td>1263</td>\n",
              "      <td>1716</td>\n",
              "      <td>2603</td>\n",
              "      <td>11</td>\n",
              "      <td>2</td>\n",
              "      <td>9</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>615</td>\n",
              "      <td>1</td>\n",
              "      <td>2.5</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>0.8</td>\n",
              "      <td>131</td>\n",
              "      <td>6</td>\n",
              "      <td>9</td>\n",
              "      <td>1216</td>\n",
              "      <td>1786</td>\n",
              "      <td>2769</td>\n",
              "      <td>16</td>\n",
              "      <td>8</td>\n",
              "      <td>11</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1821</td>\n",
              "      <td>1</td>\n",
              "      <td>1.2</td>\n",
              "      <td>0</td>\n",
              "      <td>13</td>\n",
              "      <td>1</td>\n",
              "      <td>44</td>\n",
              "      <td>0.6</td>\n",
              "      <td>141</td>\n",
              "      <td>2</td>\n",
              "      <td>14</td>\n",
              "      <td>1208</td>\n",
              "      <td>1212</td>\n",
              "      <td>1411</td>\n",
              "      <td>8</td>\n",
              "      <td>2</td>\n",
              "      <td>15</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   battery_power  blue  clock_speed  dual_sim  fc  four_g  int_memory  m_dep  \\\n",
              "0            842     0          2.2         0   1       0           7    0.6   \n",
              "1           1021     1          0.5         1   0       1          53    0.7   \n",
              "2            563     1          0.5         1   2       1          41    0.9   \n",
              "3            615     1          2.5         0   0       0          10    0.8   \n",
              "4           1821     1          1.2         0  13       1          44    0.6   \n",
              "\n",
              "   mobile_wt  n_cores  pc  px_height  px_width   ram  sc_h  sc_w  talk_time  \\\n",
              "0        188        2   2         20       756  2549     9     7         19   \n",
              "1        136        3   6        905      1988  2631    17     3          7   \n",
              "2        145        5   6       1263      1716  2603    11     2          9   \n",
              "3        131        6   9       1216      1786  2769    16     8         11   \n",
              "4        141        2  14       1208      1212  1411     8     2         15   \n",
              "\n",
              "   three_g  touch_screen  wifi  \n",
              "0        0             0     1  \n",
              "1        1             1     0  \n",
              "2        1             1     0  \n",
              "3        1             0     0  \n",
              "4        1             1     0  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "emfmQXeVtEK2",
        "outputId": "b965d04c-56c8-4fa3-9d28-334c4007e80f"
      },
      "source": [
        "y.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    1\n",
              "1    2\n",
              "2    2\n",
              "3    2\n",
              "4    1\n",
              "Name: price_range, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iQ11cHKmtEK2"
      },
      "source": [
        "from sklearn.feature_selection import SelectKBest\n",
        "from sklearn.feature_selection import chi2"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4N6mKSixtEK2",
        "outputId": "131c9037-f998-4ad5-d33b-83b76d225335"
      },
      "source": [
        "df.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(2000, 21)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KakfzulutEK4"
      },
      "source": [
        "### Apply SelectKBest Algorithm\n",
        "ordered_rank_features=SelectKBest(score_func=chi2,k=20)\n",
        "ordered_feature=ordered_rank_features.fit(X,y)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Pn-orKK2tEK4"
      },
      "source": [
        "dfscores=pd.DataFrame(ordered_feature.scores_,columns=[\"Score\"])\n",
        "dfcolumns=pd.DataFrame(X.columns)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ztaLMpsBtEK5"
      },
      "source": [
        "features_rank=pd.concat([dfcolumns,dfscores],axis=1)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "to9b8kbytEK5",
        "outputId": "f15e7c58-82c7-4e58-a964-5ee4f2864aa5"
      },
      "source": [
        "features_rank.columns=['Features','Score']\n",
        "features_rank"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
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              "    }\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>Features</th>\n",
              "      <th>Score</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>battery_power</td>\n",
              "      <td>14129.866576</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>blue</td>\n",
              "      <td>0.723232</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>clock_speed</td>\n",
              "      <td>0.648366</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>dual_sim</td>\n",
              "      <td>0.631011</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>fc</td>\n",
              "      <td>10.135166</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>four_g</td>\n",
              "      <td>1.521572</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>int_memory</td>\n",
              "      <td>89.839124</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>m_dep</td>\n",
              "      <td>0.745820</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>mobile_wt</td>\n",
              "      <td>95.972863</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>n_cores</td>\n",
              "      <td>9.097556</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>pc</td>\n",
              "      <td>9.186054</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>px_height</td>\n",
              "      <td>17363.569536</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>px_width</td>\n",
              "      <td>9810.586750</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>ram</td>\n",
              "      <td>931267.519053</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>sc_h</td>\n",
              "      <td>9.614878</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>sc_w</td>\n",
              "      <td>16.480319</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>talk_time</td>\n",
              "      <td>13.236400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>three_g</td>\n",
              "      <td>0.327643</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>touch_screen</td>\n",
              "      <td>1.928429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>wifi</td>\n",
              "      <td>0.422091</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         Features          Score\n",
              "0   battery_power   14129.866576\n",
              "1            blue       0.723232\n",
              "2     clock_speed       0.648366\n",
              "3        dual_sim       0.631011\n",
              "4              fc      10.135166\n",
              "5          four_g       1.521572\n",
              "6      int_memory      89.839124\n",
              "7           m_dep       0.745820\n",
              "8       mobile_wt      95.972863\n",
              "9         n_cores       9.097556\n",
              "10             pc       9.186054\n",
              "11      px_height   17363.569536\n",
              "12       px_width    9810.586750\n",
              "13            ram  931267.519053\n",
              "14           sc_h       9.614878\n",
              "15           sc_w      16.480319\n",
              "16      talk_time      13.236400\n",
              "17        three_g       0.327643\n",
              "18   touch_screen       1.928429\n",
              "19           wifi       0.422091"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ERGcVYAXtEK5",
        "outputId": "8c164baf-e57d-47fd-a8b6-6163bb8dc13f"
      },
      "source": [
        "features_rank.nlargest(10,'Score')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Features</th>\n",
              "      <th>Score</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>ram</td>\n",
              "      <td>931267.519053</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>px_height</td>\n",
              "      <td>17363.569536</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>battery_power</td>\n",
              "      <td>14129.866576</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>px_width</td>\n",
              "      <td>9810.586750</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>mobile_wt</td>\n",
              "      <td>95.972863</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>int_memory</td>\n",
              "      <td>89.839124</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>sc_w</td>\n",
              "      <td>16.480319</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>talk_time</td>\n",
              "      <td>13.236400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>fc</td>\n",
              "      <td>10.135166</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>sc_h</td>\n",
              "      <td>9.614878</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         Features          Score\n",
              "13            ram  931267.519053\n",
              "11      px_height   17363.569536\n",
              "0   battery_power   14129.866576\n",
              "12       px_width    9810.586750\n",
              "8       mobile_wt      95.972863\n",
              "6      int_memory      89.839124\n",
              "15           sc_w      16.480319\n",
              "16      talk_time      13.236400\n",
              "4              fc      10.135166\n",
              "14           sc_h       9.614878"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NN9jXNaotEK6"
      },
      "source": [
        "##### Feature Importance\n",
        "This technique gives you a score for each feature of your data,the higher the score mor relevant it is"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tdpClQmOtEK6",
        "outputId": "07784d87-be57-44c0-a457-2a5d03089d21"
      },
      "source": [
        "from sklearn.ensemble import ExtraTreesClassifier\n",
        "import matplotlib.pyplot as plt\n",
        "model=ExtraTreesClassifier()\n",
        "model.fit(X,y)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ExtraTreesClassifier()"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ozUwQBY2tEK7",
        "outputId": "13cc466c-aa0e-4ec5-877a-731765f2d9a5"
      },
      "source": [
        "print(model.feature_importances_)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[0.06153371 0.01935284 0.0327604  0.02021518 0.03206452 0.01764694\n",
            " 0.03493519 0.03307269 0.03599477 0.03262977 0.03336096 0.04747963\n",
            " 0.04880065 0.39576103 0.03355555 0.03306568 0.03457466 0.01388524\n",
            " 0.01851953 0.02079106]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3GDo1uu_tEK7",
        "outputId": "ac5e3f46-e412-4d4e-c635-589611612d90"
      },
      "source": [
        "ranked_features=pd.Series(model.feature_importances_,index=X.columns)\n",
        "ranked_features.nlargest(10).plot(kind='barh')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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oZ72kK1TzAWB/4HpJ10/IQYmIiKa6YYZ1MLDY9kxgM7VH0v8pcKmktwHPtP3lIfpPAVbYPpTaU4p3hNtngAttzwLeDFzcpO9ngM8Ube5v2HY4tdnUIcALgGNsf7ZoN8/2vMadSVogqSqpum3Lplbee0REtKgbAmuD7eXF8uXAHNvXAv3A54F3D9P/MWDH9abVQF+xfDxwkaS1wFXAXpIaH28/G/h2sfz1hm0rbf/C9nZgbd1+B2V7se2K7cqkydOGax4RESPQDZ/DanzksSXtBrwUeBTYB/jFEP0f987HJm9j53vaDZht+9H6xpJarWtr3XL9fiMiogO6YYY1Q9LsYvkU4CbgXODu4vVXJD19FPu9htqpRQAkHdakzQpqpwsB3tbifh8GGmdqERExwbohsO4GTpO0jtps6lpqpwH/3PYyatelPjKK/X4AqBQ3c9wFnNWkzTnAn0laCewHtHLhaTHwg9x0ERHRXtp5Nq0Dg0t9wPdtv7xD408GHrXt4gaPU2yfMB77rlQqrlar47GriIieIWm17Uqzbb1+XeYIajdmCPgN8K4O1xMREYPoaGDZHgBaml1JuhXYvWH1O2z3j2H8ZcCho+0fERHtU5oZlu2jOl1DRER0TjfcdBERETGsBFZERJRCAisiIkohgRUREaWQwIqIiFJIYEVERCkksCIiohRK8zmssunfuIm+hUs6XUZTA4vmd7qEiIgRywwrIiJKIYEVERGl0HOBJeliSYc0WX+6pIuK5TfVt5F0g6Sm3x4cERHt0XOBZfvdtu8aptmbgKeEWkREdE5XBZakPknrJV1WPHjxSknTJN0j6eCizTcknTlI/7dK+odi+WxJ9xXLB0m6qVh+YrYk6QxJP5b0I+CYYt3RwBuBT0laK+mgYvdvkbSyaH/sIOMvkFSVVN22pZVnQUZERKu6KrAKBwOLbc8ENgNnUnvU/aXFQxafafvLg/S9EdgRJscCv5R0ADAHWFbfUNJ+wMepBdUfUMyobN8MXAV80PZhtn9adHma7SOpPaX4Y80Gt73YdsV2ZdLkaaN46xERMZhuDKwNtpcXy5cDc2xfC/QDnwfePVhH2/8B7ClpKvA84OvAcdTCa1lD86OAG2z/l+3HgG8NU9d3i9+rgb7W305ERIyHbgwsN76WtBvwUuBRYJ9h+t8CnAHcQy2kjgVmA8ubtG0cayhbi9/byOfXIiLarhsDa4ak2cXyKcBNwLnA3cXrr0h6+hD9bwTOK36vAeYBW203XlS6FZgr6VnF/t5St+1hYOqY30lERIybbgysu4HTJK2jNpu6ltppwD8vHml/I/CRIfovo3Y68Ebb24AN1ELvSWw/AJxPbUb2Q+C2us3fBD4oaU3dTRcREdFBskdyVmxiSeoDvm/75R0uZcwqlYqr1Wqny4iIKBVJq203/dxrN86wIiIinqKrbh6wPQC0NLuSdCuwe8Pqd9juH++6IiKi87oqsEbC9lGdriEiItonpwQjIqIUElgREVEKCayIiCiFBFZERJRCAisiIkohgRUREaWQwIqIiFIo7eewul3/xk30LVzS6TLGbGDR/E6XEBEBZIYVERElkcCKiIhSGDawJPVJuqPVHUo6XdL+da/PkTR5tAVGRETAxMywTgf2r3t9DjCiwJI0aTwLmgiScv0vIqKNWg2sp0m6TNI6SVdKmizpo5JWSbpD0mLVnARUgCskrZV0NrXwul7S9QCSXivpFkm3Sfq2pD2L9QPFPm8CFkp64oGKkl4kafVgxRV9PylpZfHzwmL9gZKWFnUvlTRD0iRJ9xX17i1pu6TjivbLJL1Q0hRJXyne3xpJJxTbTy9q/hfgmiZ1LJBUlVTdtqXxAccRETEWrQbWwcBi2zOBzcB7gYtszyoetvgM4A9tXwlUgVNtH2b7M8D9wDzb8yRNp/a04ONtv7Jo+2d14/zO9hzbnwA2STqsWH8GcOkwNW62fSRwEfDpYt1FwFeLuq8APls8hfjHwCHAHGA1cKyk3YHn2r4X+DBwne1ZwDzgU5KmFPucDZxm+9WNBdhebLtiuzJp8rRhyo2IiJFoNbA22F5eLF9O7R/6eZJuldQPvBp4WQv7eRW1oFguaS1wGnBg3fZv1S1fDJxRnB48Gfj6MPv+Rt3v2cXy7Lp+XyvqBlgGHFf8/G2xfhawqtj+WmqzvLXADcAewIxi27W2fzXcG42IiPHV6nUYN3n9BaBie4Ok86n9oz4cUfsH/5RBtv+2bvk7wMeA64DVtn85ghob621cvww4i9rpyo8CHwTmAjfW1flm2/c8qXjpqIYaIyKiTVqdYc2QtGPWcgpwU7H8UHEN6qS6tg8DUwd5vQI4pu4a02RJL242oO3fAVcD/xe4pIUaT677fUuxfDPwtmL51Lq6bwWOBrYX46wF/oRakFGM+35JKuo8vIXxIyJiArUaWHcDp0laB+xDLUS+DPQD/8TOU2lQu9b0xeKmi2cAi4EfSLre9n9Ru4vwG8W+VgAvGWLcK6jNip5yg0MTu0u6FTgbOLdY9wFqpxXXAe8otmF7K7ChGB9qQTW1eD8AFwBPB9YVt/Rf0ML4ERExgWQPdvas8ySdB0yz/b+HaTdA7fTkQ20prAWVSsXVarXTZURElIqk1bYrzbZ17WeJJH0POIjaDR0REdHjujawbJ/YuK4Isec3rP6Q7b62FBURER3TtYHVTLMQi4iI3pAvv42IiFJIYEVERCkksCIiohQSWBERUQoJrIiIKIUEVkRElEKpbmsvk/6Nm+hbuKTTZUREtNXAovkTtu/MsCIiohQSWBERUQoJrIiIKIWeDizV9PQxiIgoi577x1pSn6S7JX0BuA34f5Kqku6U9PG6dgOS/kbSLcX2V0q6WtJPJZ3VuXcQEdGbevUuwYOBM2y/V9I+tn8laRKwVNJM2+uKdhtsz5Z0IbUHUx4D7AHcCXyxcaeSFgALACbttW873kdERM/ouRlW4ee2dzxt+K2SbgPWAC8DDqlrd1Xxux+41fbDxVOTfydp78ad2l5su2K7MmnytImsPyKi5/TqDOu3AJKeD5wHzLL9a0mXUptB7bC1+L29bnnH6149dhERHdGrM6wd9qIWXpskPQd4Q4friYiIQfT0LMH27ZLWULsmdR+wvMMlRUTEIGS70zXskiqViqvVaqfLiIgoFUmrbVeabev1U4IREVESCayIiCiFBFZERJRCAisiIkohgRUREaWQuwQniKSHgXs6XccQpgMPdbqIYXR7jalvbLq9Puj+GnfF+g603fS77Xr6c1gT7J7Bbs3sBpKq3VwfdH+NqW9sur0+6P4ae62+nBKMiIhSSGBFREQpJLAmzuJOFzCMbq8Pur/G1Dc23V4fdH+NPVVfbrqIiIhSyAwrIiJKIYEVERGlkMAaBUmvl3SPpHslLWyyXZI+W2xfJ+mVrfbtgvoGJPVLWitpQr5uvoX6XiLpFklbJZ03kr5dUN+EH78Wazy1+N92naSbJR3aat8uqK8b/gZPKGpbK6kqaU6rfbukxo4fw7p2syRtk3TSSPs+he38jOAHmAT8FHgB8N+A24FDGtr8D+AHgIBXAbe22reT9RXbBoDpHT5+zwZmAZ8AzhtJ307W147jN4IajwaeWSy/oQv/BpvW10V/g3uy8xr/TGB9u47fWGvslmNY1+464F+Bk8Z6DDPDGrkjgXtt32f7MeCbwAkNbU4AvuqaFcDekvZrsW8n62uHYeuz/aDtVcDjI+3b4frapZUab7b96+LlCuC5rfbtcH3t0Ep9j7j41xWYArjVvl1QYzu0ehzeD3wHeHAUfZ8igTVyBwAb6l7/oljXSptW+nayPqj90V8jabWkBeNcW6v1TUTfVo11jIk+fjDyGv+Y2ox6NH1HYyz1QZf8DUo6UdJ6YAnwrpH07XCN0AXHUNIBwInAF0fadzD5aqaRU5N1jf9lM1ibVvqO1VjqAzjG9v2Sng1cK2m97RvbXN9E9G3VWMeY6OMHI6hR0jxqgbDj+kZXHcMm9UGX/A3a/h7wPUnHARcAx7fadxyMpUbojmP4aeBDtrdJT2o+6mOYGdbI/QJ4Xt3r5wL3t9imlb6drA/bO34/CHyP2vS93fVNRN9WjWmMNhw/aLFGSTOBi4ETbP9yJH07WF/X/Q0W/9AfJGn6SPt2qMZuOYYV4JuSBoCTgC9IelOLfZubqItyu+oPtVnpfcDz2XnB8GUNbebz5JsaVrbat8P1TQGm1i3fDLy+3fXVtT2fJ9900RXHb4j6Jvz4jeB/4xnAvcDRo31/HaqvK/4GgRey84aGVwIbi/+/TPjxG4cau+IYNrS/lJ03XYz6GI7rQe6VH2p32f2Y2p0uHy7WnQWcVSwL+HyxvR+oDNW3W+qjdtfO7cXPnR2s779T+6+wzcBviuW9uuj4Na2vXcevxRovBn4NrC1+ql32N9i0vi76G/xQMf5a4BZgTjuP31hq7JZj2ND2UorAGssxzFczRUREKeQaVkRElEICKyIiSiGBFRERpZDAioiIUkhgRUREKSSwIiKiFBJYERFRCv8fNC2atU5KAeUAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VoMUs5cLtEK7"
      },
      "source": [
        "#### Correlation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TDiZLOP1tEK8",
        "outputId": "e34dd492-b8d9-40c3-afbb-69a586d8fd5e"
      },
      "source": [
        "df.corr()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>battery_power</th>\n",
              "      <th>blue</th>\n",
              "      <th>clock_speed</th>\n",
              "      <th>dual_sim</th>\n",
              "      <th>fc</th>\n",
              "      <th>four_g</th>\n",
              "      <th>int_memory</th>\n",
              "      <th>m_dep</th>\n",
              "      <th>mobile_wt</th>\n",
              "      <th>n_cores</th>\n",
              "      <th>...</th>\n",
              "      <th>px_height</th>\n",
              "      <th>px_width</th>\n",
              "      <th>ram</th>\n",
              "      <th>sc_h</th>\n",
              "      <th>sc_w</th>\n",
              "      <th>talk_time</th>\n",
              "      <th>three_g</th>\n",
              "      <th>touch_screen</th>\n",
              "      <th>wifi</th>\n",
              "      <th>price_range</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>battery_power</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.011252</td>\n",
              "      <td>0.011482</td>\n",
              "      <td>-0.041847</td>\n",
              "      <td>0.033334</td>\n",
              "      <td>0.015665</td>\n",
              "      <td>-0.004004</td>\n",
              "      <td>0.034085</td>\n",
              "      <td>0.001844</td>\n",
              "      <td>-0.029727</td>\n",
              "      <td>...</td>\n",
              "      <td>0.014901</td>\n",
              "      <td>-0.008402</td>\n",
              "      <td>-0.000653</td>\n",
              "      <td>-0.029959</td>\n",
              "      <td>-0.021421</td>\n",
              "      <td>0.052510</td>\n",
              "      <td>0.011522</td>\n",
              "      <td>-0.010516</td>\n",
              "      <td>-0.008343</td>\n",
              "      <td>0.200723</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>blue</th>\n",
              "      <td>0.011252</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.021419</td>\n",
              "      <td>0.035198</td>\n",
              "      <td>0.003593</td>\n",
              "      <td>0.013443</td>\n",
              "      <td>0.041177</td>\n",
              "      <td>0.004049</td>\n",
              "      <td>-0.008605</td>\n",
              "      <td>0.036161</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.006872</td>\n",
              "      <td>-0.041533</td>\n",
              "      <td>0.026351</td>\n",
              "      <td>-0.002952</td>\n",
              "      <td>0.000613</td>\n",
              "      <td>0.013934</td>\n",
              "      <td>-0.030236</td>\n",
              "      <td>0.010061</td>\n",
              "      <td>-0.021863</td>\n",
              "      <td>0.020573</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>clock_speed</th>\n",
              "      <td>0.011482</td>\n",
              "      <td>0.021419</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.001315</td>\n",
              "      <td>-0.000434</td>\n",
              "      <td>-0.043073</td>\n",
              "      <td>0.006545</td>\n",
              "      <td>-0.014364</td>\n",
              "      <td>0.012350</td>\n",
              "      <td>-0.005724</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.014523</td>\n",
              "      <td>-0.009476</td>\n",
              "      <td>0.003443</td>\n",
              "      <td>-0.029078</td>\n",
              "      <td>-0.007378</td>\n",
              "      <td>-0.011432</td>\n",
              "      <td>-0.046433</td>\n",
              "      <td>0.019756</td>\n",
              "      <td>-0.024471</td>\n",
              "      <td>-0.006606</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dual_sim</th>\n",
              "      <td>-0.041847</td>\n",
              "      <td>0.035198</td>\n",
              "      <td>-0.001315</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.029123</td>\n",
              "      <td>0.003187</td>\n",
              "      <td>-0.015679</td>\n",
              "      <td>-0.022142</td>\n",
              "      <td>-0.008979</td>\n",
              "      <td>-0.024658</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.020875</td>\n",
              "      <td>0.014291</td>\n",
              "      <td>0.041072</td>\n",
              "      <td>-0.011949</td>\n",
              "      <td>-0.016666</td>\n",
              "      <td>-0.039404</td>\n",
              "      <td>-0.014008</td>\n",
              "      <td>-0.017117</td>\n",
              "      <td>0.022740</td>\n",
              "      <td>0.017444</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>fc</th>\n",
              "      <td>0.033334</td>\n",
              "      <td>0.003593</td>\n",
              "      <td>-0.000434</td>\n",
              "      <td>-0.029123</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.016560</td>\n",
              "      <td>-0.029133</td>\n",
              "      <td>-0.001791</td>\n",
              "      <td>0.023618</td>\n",
              "      <td>-0.013356</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.009990</td>\n",
              "      <td>-0.005176</td>\n",
              "      <td>0.015099</td>\n",
              "      <td>-0.011014</td>\n",
              "      <td>-0.012373</td>\n",
              "      <td>-0.006829</td>\n",
              "      <td>0.001793</td>\n",
              "      <td>-0.014828</td>\n",
              "      <td>0.020085</td>\n",
              "      <td>0.021998</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>four_g</th>\n",
              "      <td>0.015665</td>\n",
              "      <td>0.013443</td>\n",
              "      <td>-0.043073</td>\n",
              "      <td>0.003187</td>\n",
              "      <td>-0.016560</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.008690</td>\n",
              "      <td>-0.001823</td>\n",
              "      <td>-0.016537</td>\n",
              "      <td>-0.029706</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.019236</td>\n",
              "      <td>0.007448</td>\n",
              "      <td>0.007313</td>\n",
              "      <td>0.027166</td>\n",
              "      <td>0.037005</td>\n",
              "      <td>-0.046628</td>\n",
              "      <td>0.584246</td>\n",
              "      <td>0.016758</td>\n",
              "      <td>-0.017620</td>\n",
              "      <td>0.014772</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>int_memory</th>\n",
              "      <td>-0.004004</td>\n",
              "      <td>0.041177</td>\n",
              "      <td>0.006545</td>\n",
              "      <td>-0.015679</td>\n",
              "      <td>-0.029133</td>\n",
              "      <td>0.008690</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.006886</td>\n",
              "      <td>-0.034214</td>\n",
              "      <td>-0.028310</td>\n",
              "      <td>...</td>\n",
              "      <td>0.010441</td>\n",
              "      <td>-0.008335</td>\n",
              "      <td>0.032813</td>\n",
              "      <td>0.037771</td>\n",
              "      <td>0.011731</td>\n",
              "      <td>-0.002790</td>\n",
              "      <td>-0.009366</td>\n",
              "      <td>-0.026999</td>\n",
              "      <td>0.006993</td>\n",
              "      <td>0.044435</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>m_dep</th>\n",
              "      <td>0.034085</td>\n",
              "      <td>0.004049</td>\n",
              "      <td>-0.014364</td>\n",
              "      <td>-0.022142</td>\n",
              "      <td>-0.001791</td>\n",
              "      <td>-0.001823</td>\n",
              "      <td>0.006886</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.021756</td>\n",
              "      <td>-0.003504</td>\n",
              "      <td>...</td>\n",
              "      <td>0.025263</td>\n",
              "      <td>0.023566</td>\n",
              "      <td>-0.009434</td>\n",
              "      <td>-0.025348</td>\n",
              "      <td>-0.018388</td>\n",
              "      <td>0.017003</td>\n",
              "      <td>-0.012065</td>\n",
              "      <td>-0.002638</td>\n",
              "      <td>-0.028353</td>\n",
              "      <td>0.000853</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mobile_wt</th>\n",
              "      <td>0.001844</td>\n",
              "      <td>-0.008605</td>\n",
              "      <td>0.012350</td>\n",
              "      <td>-0.008979</td>\n",
              "      <td>0.023618</td>\n",
              "      <td>-0.016537</td>\n",
              "      <td>-0.034214</td>\n",
              "      <td>0.021756</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.018989</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000939</td>\n",
              "      <td>0.000090</td>\n",
              "      <td>-0.002581</td>\n",
              "      <td>-0.033855</td>\n",
              "      <td>-0.020761</td>\n",
              "      <td>0.006209</td>\n",
              "      <td>0.001551</td>\n",
              "      <td>-0.014368</td>\n",
              "      <td>-0.000409</td>\n",
              "      <td>-0.030302</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>n_cores</th>\n",
              "      <td>-0.029727</td>\n",
              "      <td>0.036161</td>\n",
              "      <td>-0.005724</td>\n",
              "      <td>-0.024658</td>\n",
              "      <td>-0.013356</td>\n",
              "      <td>-0.029706</td>\n",
              "      <td>-0.028310</td>\n",
              "      <td>-0.003504</td>\n",
              "      <td>-0.018989</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.006872</td>\n",
              "      <td>0.024480</td>\n",
              "      <td>0.004868</td>\n",
              "      <td>-0.000315</td>\n",
              "      <td>0.025826</td>\n",
              "      <td>0.013148</td>\n",
              "      <td>-0.014733</td>\n",
              "      <td>0.023774</td>\n",
              "      <td>-0.009964</td>\n",
              "      <td>0.004399</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>pc</th>\n",
              "      <td>0.031441</td>\n",
              "      <td>-0.009952</td>\n",
              "      <td>-0.005245</td>\n",
              "      <td>-0.017143</td>\n",
              "      <td>0.644595</td>\n",
              "      <td>-0.005598</td>\n",
              "      <td>-0.033273</td>\n",
              "      <td>0.026282</td>\n",
              "      <td>0.018844</td>\n",
              "      <td>-0.001193</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.018465</td>\n",
              "      <td>0.004196</td>\n",
              "      <td>0.028984</td>\n",
              "      <td>0.004938</td>\n",
              "      <td>-0.023819</td>\n",
              "      <td>0.014657</td>\n",
              "      <td>-0.001322</td>\n",
              "      <td>-0.008742</td>\n",
              "      <td>0.005389</td>\n",
              "      <td>0.033599</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>px_height</th>\n",
              "      <td>0.014901</td>\n",
              "      <td>-0.006872</td>\n",
              "      <td>-0.014523</td>\n",
              "      <td>-0.020875</td>\n",
              "      <td>-0.009990</td>\n",
              "      <td>-0.019236</td>\n",
              "      <td>0.010441</td>\n",
              "      <td>0.025263</td>\n",
              "      <td>0.000939</td>\n",
              "      <td>-0.006872</td>\n",
              "      <td>...</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.510664</td>\n",
              "      <td>-0.020352</td>\n",
              "      <td>0.059615</td>\n",
              "      <td>0.043038</td>\n",
              "      <td>-0.010645</td>\n",
              "      <td>-0.031174</td>\n",
              "      <td>0.021891</td>\n",
              "      <td>0.051824</td>\n",
              "      <td>0.148858</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>px_width</th>\n",
              "      <td>-0.008402</td>\n",
              "      <td>-0.041533</td>\n",
              "      <td>-0.009476</td>\n",
              "      <td>0.014291</td>\n",
              "      <td>-0.005176</td>\n",
              "      <td>0.007448</td>\n",
              "      <td>-0.008335</td>\n",
              "      <td>0.023566</td>\n",
              "      <td>0.000090</td>\n",
              "      <td>0.024480</td>\n",
              "      <td>...</td>\n",
              "      <td>0.510664</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.004105</td>\n",
              "      <td>0.021599</td>\n",
              "      <td>0.034699</td>\n",
              "      <td>0.006720</td>\n",
              "      <td>0.000350</td>\n",
              "      <td>-0.001628</td>\n",
              "      <td>0.030319</td>\n",
              "      <td>0.165818</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ram</th>\n",
              "      <td>-0.000653</td>\n",
              "      <td>0.026351</td>\n",
              "      <td>0.003443</td>\n",
              "      <td>0.041072</td>\n",
              "      <td>0.015099</td>\n",
              "      <td>0.007313</td>\n",
              "      <td>0.032813</td>\n",
              "      <td>-0.009434</td>\n",
              "      <td>-0.002581</td>\n",
              "      <td>0.004868</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.020352</td>\n",
              "      <td>0.004105</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.015996</td>\n",
              "      <td>0.035576</td>\n",
              "      <td>0.010820</td>\n",
              "      <td>0.015795</td>\n",
              "      <td>-0.030455</td>\n",
              "      <td>0.022669</td>\n",
              "      <td>0.917046</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sc_h</th>\n",
              "      <td>-0.029959</td>\n",
              "      <td>-0.002952</td>\n",
              "      <td>-0.029078</td>\n",
              "      <td>-0.011949</td>\n",
              "      <td>-0.011014</td>\n",
              "      <td>0.027166</td>\n",
              "      <td>0.037771</td>\n",
              "      <td>-0.025348</td>\n",
              "      <td>-0.033855</td>\n",
              "      <td>-0.000315</td>\n",
              "      <td>...</td>\n",
              "      <td>0.059615</td>\n",
              "      <td>0.021599</td>\n",
              "      <td>0.015996</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.506144</td>\n",
              "      <td>-0.017335</td>\n",
              "      <td>0.012033</td>\n",
              "      <td>-0.020023</td>\n",
              "      <td>0.025929</td>\n",
              "      <td>0.022986</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>sc_w</th>\n",
              "      <td>-0.021421</td>\n",
              "      <td>0.000613</td>\n",
              "      <td>-0.007378</td>\n",
              "      <td>-0.016666</td>\n",
              "      <td>-0.012373</td>\n",
              "      <td>0.037005</td>\n",
              "      <td>0.011731</td>\n",
              "      <td>-0.018388</td>\n",
              "      <td>-0.020761</td>\n",
              "      <td>0.025826</td>\n",
              "      <td>...</td>\n",
              "      <td>0.043038</td>\n",
              "      <td>0.034699</td>\n",
              "      <td>0.035576</td>\n",
              "      <td>0.506144</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.022821</td>\n",
              "      <td>0.030941</td>\n",
              "      <td>0.012720</td>\n",
              "      <td>0.035423</td>\n",
              "      <td>0.038711</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>talk_time</th>\n",
              "      <td>0.052510</td>\n",
              "      <td>0.013934</td>\n",
              "      <td>-0.011432</td>\n",
              "      <td>-0.039404</td>\n",
              "      <td>-0.006829</td>\n",
              "      <td>-0.046628</td>\n",
              "      <td>-0.002790</td>\n",
              "      <td>0.017003</td>\n",
              "      <td>0.006209</td>\n",
              "      <td>0.013148</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.010645</td>\n",
              "      <td>0.006720</td>\n",
              "      <td>0.010820</td>\n",
              "      <td>-0.017335</td>\n",
              "      <td>-0.022821</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.042688</td>\n",
              "      <td>0.017196</td>\n",
              "      <td>-0.029504</td>\n",
              "      <td>0.021859</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>three_g</th>\n",
              "      <td>0.011522</td>\n",
              "      <td>-0.030236</td>\n",
              "      <td>-0.046433</td>\n",
              "      <td>-0.014008</td>\n",
              "      <td>0.001793</td>\n",
              "      <td>0.584246</td>\n",
              "      <td>-0.009366</td>\n",
              "      <td>-0.012065</td>\n",
              "      <td>0.001551</td>\n",
              "      <td>-0.014733</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.031174</td>\n",
              "      <td>0.000350</td>\n",
              "      <td>0.015795</td>\n",
              "      <td>0.012033</td>\n",
              "      <td>0.030941</td>\n",
              "      <td>-0.042688</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.013917</td>\n",
              "      <td>0.004316</td>\n",
              "      <td>0.023611</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>touch_screen</th>\n",
              "      <td>-0.010516</td>\n",
              "      <td>0.010061</td>\n",
              "      <td>0.019756</td>\n",
              "      <td>-0.017117</td>\n",
              "      <td>-0.014828</td>\n",
              "      <td>0.016758</td>\n",
              "      <td>-0.026999</td>\n",
              "      <td>-0.002638</td>\n",
              "      <td>-0.014368</td>\n",
              "      <td>0.023774</td>\n",
              "      <td>...</td>\n",
              "      <td>0.021891</td>\n",
              "      <td>-0.001628</td>\n",
              "      <td>-0.030455</td>\n",
              "      <td>-0.020023</td>\n",
              "      <td>0.012720</td>\n",
              "      <td>0.017196</td>\n",
              "      <td>0.013917</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.011917</td>\n",
              "      <td>-0.030411</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>wifi</th>\n",
              "      <td>-0.008343</td>\n",
              "      <td>-0.021863</td>\n",
              "      <td>-0.024471</td>\n",
              "      <td>0.022740</td>\n",
              "      <td>0.020085</td>\n",
              "      <td>-0.017620</td>\n",
              "      <td>0.006993</td>\n",
              "      <td>-0.028353</td>\n",
              "      <td>-0.000409</td>\n",
              "      <td>-0.009964</td>\n",
              "      <td>...</td>\n",
              "      <td>0.051824</td>\n",
              "      <td>0.030319</td>\n",
              "      <td>0.022669</td>\n",
              "      <td>0.025929</td>\n",
              "      <td>0.035423</td>\n",
              "      <td>-0.029504</td>\n",
              "      <td>0.004316</td>\n",
              "      <td>0.011917</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.018785</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>price_range</th>\n",
              "      <td>0.200723</td>\n",
              "      <td>0.020573</td>\n",
              "      <td>-0.006606</td>\n",
              "      <td>0.017444</td>\n",
              "      <td>0.021998</td>\n",
              "      <td>0.014772</td>\n",
              "      <td>0.044435</td>\n",
              "      <td>0.000853</td>\n",
              "      <td>-0.030302</td>\n",
              "      <td>0.004399</td>\n",
              "      <td>...</td>\n",
              "      <td>0.148858</td>\n",
              "      <td>0.165818</td>\n",
              "      <td>0.917046</td>\n",
              "      <td>0.022986</td>\n",
              "      <td>0.038711</td>\n",
              "      <td>0.021859</td>\n",
              "      <td>0.023611</td>\n",
              "      <td>-0.030411</td>\n",
              "      <td>0.018785</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>21 rows × 21 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "               battery_power      blue  clock_speed  dual_sim        fc  \\\n",
              "battery_power       1.000000  0.011252     0.011482 -0.041847  0.033334   \n",
              "blue                0.011252  1.000000     0.021419  0.035198  0.003593   \n",
              "clock_speed         0.011482  0.021419     1.000000 -0.001315 -0.000434   \n",
              "dual_sim           -0.041847  0.035198    -0.001315  1.000000 -0.029123   \n",
              "fc                  0.033334  0.003593    -0.000434 -0.029123  1.000000   \n",
              "four_g              0.015665  0.013443    -0.043073  0.003187 -0.016560   \n",
              "int_memory         -0.004004  0.041177     0.006545 -0.015679 -0.029133   \n",
              "m_dep               0.034085  0.004049    -0.014364 -0.022142 -0.001791   \n",
              "mobile_wt           0.001844 -0.008605     0.012350 -0.008979  0.023618   \n",
              "n_cores            -0.029727  0.036161    -0.005724 -0.024658 -0.013356   \n",
              "pc                  0.031441 -0.009952    -0.005245 -0.017143  0.644595   \n",
              "px_height           0.014901 -0.006872    -0.014523 -0.020875 -0.009990   \n",
              "px_width           -0.008402 -0.041533    -0.009476  0.014291 -0.005176   \n",
              "ram                -0.000653  0.026351     0.003443  0.041072  0.015099   \n",
              "sc_h               -0.029959 -0.002952    -0.029078 -0.011949 -0.011014   \n",
              "sc_w               -0.021421  0.000613    -0.007378 -0.016666 -0.012373   \n",
              "talk_time           0.052510  0.013934    -0.011432 -0.039404 -0.006829   \n",
              "three_g             0.011522 -0.030236    -0.046433 -0.014008  0.001793   \n",
              "touch_screen       -0.010516  0.010061     0.019756 -0.017117 -0.014828   \n",
              "wifi               -0.008343 -0.021863    -0.024471  0.022740  0.020085   \n",
              "price_range         0.200723  0.020573    -0.006606  0.017444  0.021998   \n",
              "\n",
              "                 four_g  int_memory     m_dep  mobile_wt   n_cores  ...  \\\n",
              "battery_power  0.015665   -0.004004  0.034085   0.001844 -0.029727  ...   \n",
              "blue           0.013443    0.041177  0.004049  -0.008605  0.036161  ...   \n",
              "clock_speed   -0.043073    0.006545 -0.014364   0.012350 -0.005724  ...   \n",
              "dual_sim       0.003187   -0.015679 -0.022142  -0.008979 -0.024658  ...   \n",
              "fc            -0.016560   -0.029133 -0.001791   0.023618 -0.013356  ...   \n",
              "four_g         1.000000    0.008690 -0.001823  -0.016537 -0.029706  ...   \n",
              "int_memory     0.008690    1.000000  0.006886  -0.034214 -0.028310  ...   \n",
              "m_dep         -0.001823    0.006886  1.000000   0.021756 -0.003504  ...   \n",
              "mobile_wt     -0.016537   -0.034214  0.021756   1.000000 -0.018989  ...   \n",
              "n_cores       -0.029706   -0.028310 -0.003504  -0.018989  1.000000  ...   \n",
              "pc            -0.005598   -0.033273  0.026282   0.018844 -0.001193  ...   \n",
              "px_height     -0.019236    0.010441  0.025263   0.000939 -0.006872  ...   \n",
              "px_width       0.007448   -0.008335  0.023566   0.000090  0.024480  ...   \n",
              "ram            0.007313    0.032813 -0.009434  -0.002581  0.004868  ...   \n",
              "sc_h           0.027166    0.037771 -0.025348  -0.033855 -0.000315  ...   \n",
              "sc_w           0.037005    0.011731 -0.018388  -0.020761  0.025826  ...   \n",
              "talk_time     -0.046628   -0.002790  0.017003   0.006209  0.013148  ...   \n",
              "three_g        0.584246   -0.009366 -0.012065   0.001551 -0.014733  ...   \n",
              "touch_screen   0.016758   -0.026999 -0.002638  -0.014368  0.023774  ...   \n",
              "wifi          -0.017620    0.006993 -0.028353  -0.000409 -0.009964  ...   \n",
              "price_range    0.014772    0.044435  0.000853  -0.030302  0.004399  ...   \n",
              "\n",
              "               px_height  px_width       ram      sc_h      sc_w  talk_time  \\\n",
              "battery_power   0.014901 -0.008402 -0.000653 -0.029959 -0.021421   0.052510   \n",
              "blue           -0.006872 -0.041533  0.026351 -0.002952  0.000613   0.013934   \n",
              "clock_speed    -0.014523 -0.009476  0.003443 -0.029078 -0.007378  -0.011432   \n",
              "dual_sim       -0.020875  0.014291  0.041072 -0.011949 -0.016666  -0.039404   \n",
              "fc             -0.009990 -0.005176  0.015099 -0.011014 -0.012373  -0.006829   \n",
              "four_g         -0.019236  0.007448  0.007313  0.027166  0.037005  -0.046628   \n",
              "int_memory      0.010441 -0.008335  0.032813  0.037771  0.011731  -0.002790   \n",
              "m_dep           0.025263  0.023566 -0.009434 -0.025348 -0.018388   0.017003   \n",
              "mobile_wt       0.000939  0.000090 -0.002581 -0.033855 -0.020761   0.006209   \n",
              "n_cores        -0.006872  0.024480  0.004868 -0.000315  0.025826   0.013148   \n",
              "pc             -0.018465  0.004196  0.028984  0.004938 -0.023819   0.014657   \n",
              "px_height       1.000000  0.510664 -0.020352  0.059615  0.043038  -0.010645   \n",
              "px_width        0.510664  1.000000  0.004105  0.021599  0.034699   0.006720   \n",
              "ram            -0.020352  0.004105  1.000000  0.015996  0.035576   0.010820   \n",
              "sc_h            0.059615  0.021599  0.015996  1.000000  0.506144  -0.017335   \n",
              "sc_w            0.043038  0.034699  0.035576  0.506144  1.000000  -0.022821   \n",
              "talk_time      -0.010645  0.006720  0.010820 -0.017335 -0.022821   1.000000   \n",
              "three_g        -0.031174  0.000350  0.015795  0.012033  0.030941  -0.042688   \n",
              "touch_screen    0.021891 -0.001628 -0.030455 -0.020023  0.012720   0.017196   \n",
              "wifi            0.051824  0.030319  0.022669  0.025929  0.035423  -0.029504   \n",
              "price_range     0.148858  0.165818  0.917046  0.022986  0.038711   0.021859   \n",
              "\n",
              "                three_g  touch_screen      wifi  price_range  \n",
              "battery_power  0.011522     -0.010516 -0.008343     0.200723  \n",
              "blue          -0.030236      0.010061 -0.021863     0.020573  \n",
              "clock_speed   -0.046433      0.019756 -0.024471    -0.006606  \n",
              "dual_sim      -0.014008     -0.017117  0.022740     0.017444  \n",
              "fc             0.001793     -0.014828  0.020085     0.021998  \n",
              "four_g         0.584246      0.016758 -0.017620     0.014772  \n",
              "int_memory    -0.009366     -0.026999  0.006993     0.044435  \n",
              "m_dep         -0.012065     -0.002638 -0.028353     0.000853  \n",
              "mobile_wt      0.001551     -0.014368 -0.000409    -0.030302  \n",
              "n_cores       -0.014733      0.023774 -0.009964     0.004399  \n",
              "pc            -0.001322     -0.008742  0.005389     0.033599  \n",
              "px_height     -0.031174      0.021891  0.051824     0.148858  \n",
              "px_width       0.000350     -0.001628  0.030319     0.165818  \n",
              "ram            0.015795     -0.030455  0.022669     0.917046  \n",
              "sc_h           0.012033     -0.020023  0.025929     0.022986  \n",
              "sc_w           0.030941      0.012720  0.035423     0.038711  \n",
              "talk_time     -0.042688      0.017196 -0.029504     0.021859  \n",
              "three_g        1.000000      0.013917  0.004316     0.023611  \n",
              "touch_screen   0.013917      1.000000  0.011917    -0.030411  \n",
              "wifi           0.004316      0.011917  1.000000     0.018785  \n",
              "price_range    0.023611     -0.030411  0.018785     1.000000  \n",
              "\n",
              "[21 rows x 21 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JMN738z6tEK8",
        "outputId": "bffe879c-9969-403a-875a-2f761cb8ff08"
      },
      "source": [
        "import seaborn as sns\n",
        "corr=df.iloc[:,:-1].corr()\n",
        "top_features=corr.index\n",
        "plt.figure(figsize=(20,20))\n",
        "sns.heatmap(df[top_features].corr(),annot=True)\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x1c5a0bbbf60>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x1440 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZMJU2U3ItEK8"
      },
      "source": [
        "#### Remove The correlated"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5HaUeMdmtEK8"
      },
      "source": [
        "threshold=0.8"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "h2x8A9NdtEK9"
      },
      "source": [
        "# find and remove correlated features\n",
        "def correlation(dataset, threshold):\n",
        "    col_corr = set()  # Set of all the names of correlated columns\n",
        "    corr_matrix = dataset.corr()\n",
        "    for i in range(len(corr_matrix.columns)):\n",
        "        for j in range(i):\n",
        "            if abs(corr_matrix.iloc[i, j]) > threshold: # we are interested in absolute coeff value\n",
        "                colname = corr_matrix.columns[i]  # getting the name of column\n",
        "                col_corr.add(colname)\n",
        "    return col_corr"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FHelFl8NtEK9",
        "outputId": "5a639bc9-a179-4741-f8c9-374285405206"
      },
      "source": [
        "correlation(df.iloc[:,:-1],threshold)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "set()"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yDzJ_AI3tEK9"
      },
      "source": [
        "#### Information Gain"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pfvVOduqtEK-"
      },
      "source": [
        "from sklearn.feature_selection import mutual_info_classif"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9jZV902mtEK-"
      },
      "source": [
        "mutual_info=mutual_info_classif(X,y)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VYGSYshwtEK-",
        "outputId": "5b1cadca-511f-487e-f88b-e8e3c44edcc3"
      },
      "source": [
        "mutual_data=pd.Series(mutual_info,index=X.columns)\n",
        "mutual_data.sort_values(ascending=False)\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ram              0.848254\n",
              "sc_w             0.032774\n",
              "int_memory       0.029968\n",
              "battery_power    0.027203\n",
              "px_width         0.024848\n",
              "fc               0.023923\n",
              "dual_sim         0.022537\n",
              "px_height        0.022146\n",
              "mobile_wt        0.013782\n",
              "touch_screen     0.012663\n",
              "clock_speed      0.010944\n",
              "n_cores          0.009517\n",
              "four_g           0.008748\n",
              "m_dep            0.000000\n",
              "pc               0.000000\n",
              "sc_h             0.000000\n",
              "talk_time        0.000000\n",
              "three_g          0.000000\n",
              "blue             0.000000\n",
              "wifi             0.000000\n",
              "dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        }
      ]
    }
  ]
}