Machine_Learning/Heart Disease Prediction [END 2 END]/Heart Disease Prediction.ipynb

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   "source": [
    "# Importing essential libraries\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "JpIAT4StTd2m"
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   "source": [
    "# Loading the dataset\n",
    "df = pd.read_csv('heart.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
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   "source": [
    "# **Exploring the dataset**"
   ]
  },
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   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
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       "(303, 14)"
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     "execution_count": 3,
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   "source": [
    "# Returns number of rows and columns of the dataset\n",
    "df.shape"
   ]
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       "Index(['age', 'sex', 'cp', 'trestbps', 'chol', 'fbs', 'restecg', 'thalach',\n",
       "       'exang', 'oldpeak', 'slope', 'ca', 'thal', 'target'],\n",
       "      dtype='object')"
      ]
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     "execution_count": 4,
     "metadata": {},
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   "source": [
    "# Returns an object with all of the column headers\n",
    "df.columns"
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       "age           int64\n",
       "sex           int64\n",
       "cp            int64\n",
       "trestbps      int64\n",
       "chol          int64\n",
       "fbs           int64\n",
       "restecg       int64\n",
       "thalach       int64\n",
       "exang         int64\n",
       "oldpeak     float64\n",
       "slope         int64\n",
       "ca            int64\n",
       "thal          int64\n",
       "target        int64\n",
       "dtype: object"
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    "# Returns different datatypes for each columns (float, int, string, bool, etc.)\n",
    "df.dtypes"
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       "   age  sex  cp  trestbps  chol  fbs  restecg  thalach  exang  oldpeak  slope  \\\n",
       "0   63    1   3       145   233    1        0      150      0      2.3      0   \n",
       "1   37    1   2       130   250    0        1      187      0      3.5      0   \n",
       "2   41    0   1       130   204    0        0      172      0      1.4      2   \n",
       "3   56    1   1       120   236    0        1      178      0      0.8      2   \n",
       "4   57    0   0       120   354    0        1      163      1      0.6      2   \n",
       "\n",
       "   ca  thal  target  \n",
       "0   0     1       1  \n",
       "1   0     2       1  \n",
       "2   0     2       1  \n",
       "3   0     2       1  \n",
       "4   0     2       1  "
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    "# Returns the first x number of rows when head(x). Without a number it returns 5\n",
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       "     age  sex  cp  trestbps  chol  fbs  restecg  thalach  exang  oldpeak  \\\n",
       "298   57    0   0       140   241    0        1      123      1      0.2   \n",
       "299   45    1   3       110   264    0        1      132      0      1.2   \n",
       "300   68    1   0       144   193    1        1      141      0      3.4   \n",
       "301   57    1   0       130   131    0        1      115      1      1.2   \n",
       "302   57    0   1       130   236    0        0      174      0      0.0   \n",
       "\n",
       "     slope  ca  thal  target  \n",
       "298      1   0     3       0  \n",
       "299      1   0     3       0  \n",
       "300      1   2     3       0  \n",
       "301      1   1     3       0  \n",
       "302      1   1     2       0  "
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    "# Returns the last x number of rows when tail(x). Without a number it returns 5\n",
    "df.tail()"
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       "age         False\n",
       "sex         False\n",
       "cp          False\n",
       "trestbps    False\n",
       "chol        False\n",
       "fbs         False\n",
       "restecg     False\n",
       "thalach     False\n",
       "exang       False\n",
       "oldpeak     False\n",
       "slope       False\n",
       "ca          False\n",
       "thal        False\n",
       "target      False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "# Returns true for a column having null values, else false\n",
    "df.isnull().any()"
   ]
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     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 303 entries, 0 to 302\n",
      "Data columns (total 14 columns):\n",
      "age         303 non-null int64\n",
      "sex         303 non-null int64\n",
      "cp          303 non-null int64\n",
      "trestbps    303 non-null int64\n",
      "chol        303 non-null int64\n",
      "fbs         303 non-null int64\n",
      "restecg     303 non-null int64\n",
      "thalach     303 non-null int64\n",
      "exang       303 non-null int64\n",
      "oldpeak     303 non-null float64\n",
      "slope       303 non-null int64\n",
      "ca          303 non-null int64\n",
      "thal        303 non-null int64\n",
      "target      303 non-null int64\n",
      "dtypes: float64(1), int64(13)\n",
      "memory usage: 33.3 KB\n"
     ]
    }
   ],
   "source": [
    "# Returns basic information on all columns\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
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       "      <td>age</td>\n",
       "      <td>303.0</td>\n",
       "      <td>54.366337</td>\n",
       "      <td>9.082101</td>\n",
       "      <td>29.0</td>\n",
       "      <td>47.5</td>\n",
       "      <td>55.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>77.0</td>\n",
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       "      <td>sex</td>\n",
       "      <td>303.0</td>\n",
       "      <td>0.683168</td>\n",
       "      <td>0.466011</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>cp</td>\n",
       "      <td>303.0</td>\n",
       "      <td>0.966997</td>\n",
       "      <td>1.032052</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>trestbps</td>\n",
       "      <td>303.0</td>\n",
       "      <td>131.623762</td>\n",
       "      <td>17.538143</td>\n",
       "      <td>94.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>chol</td>\n",
       "      <td>303.0</td>\n",
       "      <td>246.264026</td>\n",
       "      <td>51.830751</td>\n",
       "      <td>126.0</td>\n",
       "      <td>211.0</td>\n",
       "      <td>240.0</td>\n",
       "      <td>274.5</td>\n",
       "      <td>564.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>fbs</td>\n",
       "      <td>303.0</td>\n",
       "      <td>0.148515</td>\n",
       "      <td>0.356198</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>restecg</td>\n",
       "      <td>303.0</td>\n",
       "      <td>0.528053</td>\n",
       "      <td>0.525860</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>thalach</td>\n",
       "      <td>303.0</td>\n",
       "      <td>149.646865</td>\n",
       "      <td>22.905161</td>\n",
       "      <td>71.0</td>\n",
       "      <td>133.5</td>\n",
       "      <td>153.0</td>\n",
       "      <td>166.0</td>\n",
       "      <td>202.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>exang</td>\n",
       "      <td>303.0</td>\n",
       "      <td>0.326733</td>\n",
       "      <td>0.469794</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>oldpeak</td>\n",
       "      <td>303.0</td>\n",
       "      <td>1.039604</td>\n",
       "      <td>1.161075</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>1.6</td>\n",
       "      <td>6.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>slope</td>\n",
       "      <td>303.0</td>\n",
       "      <td>1.399340</td>\n",
       "      <td>0.616226</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>ca</td>\n",
       "      <td>303.0</td>\n",
       "      <td>0.729373</td>\n",
       "      <td>1.022606</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>thal</td>\n",
       "      <td>303.0</td>\n",
       "      <td>2.313531</td>\n",
       "      <td>0.612277</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>target</td>\n",
       "      <td>303.0</td>\n",
       "      <td>0.544554</td>\n",
       "      <td>0.498835</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          count        mean        std    min    25%    50%    75%    max\n",
       "age       303.0   54.366337   9.082101   29.0   47.5   55.0   61.0   77.0\n",
       "sex       303.0    0.683168   0.466011    0.0    0.0    1.0    1.0    1.0\n",
       "cp        303.0    0.966997   1.032052    0.0    0.0    1.0    2.0    3.0\n",
       "trestbps  303.0  131.623762  17.538143   94.0  120.0  130.0  140.0  200.0\n",
       "chol      303.0  246.264026  51.830751  126.0  211.0  240.0  274.5  564.0\n",
       "fbs       303.0    0.148515   0.356198    0.0    0.0    0.0    0.0    1.0\n",
       "restecg   303.0    0.528053   0.525860    0.0    0.0    1.0    1.0    2.0\n",
       "thalach   303.0  149.646865  22.905161   71.0  133.5  153.0  166.0  202.0\n",
       "exang     303.0    0.326733   0.469794    0.0    0.0    0.0    1.0    1.0\n",
       "oldpeak   303.0    1.039604   1.161075    0.0    0.0    0.8    1.6    6.2\n",
       "slope     303.0    1.399340   0.616226    0.0    1.0    1.0    2.0    2.0\n",
       "ca        303.0    0.729373   1.022606    0.0    0.0    0.0    1.0    4.0\n",
       "thal      303.0    2.313531   0.612277    0.0    2.0    2.0    3.0    3.0\n",
       "target    303.0    0.544554   0.498835    0.0    0.0    1.0    1.0    1.0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Returns basic statistics on numeric columns\n",
    "df.describe().T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "cVlUJwidVjLr"
   },
   "source": [
    "# **Data Visualization**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "eBqQ2CkTWBlj"
   },
   "outputs": [],
   "source": [
    "# Importing essential libraries\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 0
    },
    "colab_type": "code",
    "id": "EMtmzTXUVp37",
    "outputId": "62cd0d7f-408d-417a-bdea-c3ee30ff0e38"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:4: UserWarning: To output multiple subplots, the figure containing the passed axes is being cleared\n",
      "  after removing the cwd from sys.path.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting histogram for the entire dataset\n",
    "fig = plt.figure(figsize = (15,15))\n",
    "ax = fig.gca()\n",
    "g = df.hist(ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 0
    },
    "colab_type": "code",
    "id": "hMpcT5VsWtGP",
    "outputId": "647aa5e5-f26f-43f8-f36a-cc029d930c82"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Count')"
      ]
     },
     "execution_count": 13,
     "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": [
    "# Visualization to check if the dataset is balanced or not\n",
    "g = sns.countplot(x='target', data=df)\n",
    "plt.xlabel('Target')\n",
    "plt.ylabel('Count')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "7xYk6MvkVH_b"
   },
   "source": [
    "# **Feature Engineering**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "iDJlzXOTVLvD"
   },
   "source": [
    "### Feature Selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "colab_type": "code",
    "id": "CJr1KF-2VLHM",
    "outputId": "584775fb-1543-4e67-f967-cc11d2dcc397"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x27c550e7b88>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Selecting correlated features using Heatmap\n",
    "\n",
    "# Get correlation of all the features of the dataset\n",
    "corr_matrix = df.corr()\n",
    "top_corr_features = corr_matrix.index\n",
    "\n",
    "# Plotting the heatmap\n",
    "plt.figure(figsize=(20,20))\n",
    "sns.heatmap(data=df[top_corr_features].corr(), annot=True, cmap='RdYlGn')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "j1bd0Qd7adPW"
   },
   "source": [
    "# **Data Preprocessing**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "ReYV5nD0cdVE"
   },
   "source": [
    "## Handling categorical features\n",
    "\n",
    "After exploring the dataset, I observed that converting the categorical variables into dummy variables using 'get_dummies()'. Though we don't have any strings in our dataset it is necessary to convert ('sex', 'cp', 'fbs', 'restecg', 'exang', 'slope', 'ca', 'thal') these features.\n",
    "\n",
    "*Example: Consider the 'sex' column, it is a binary feature which has 0's and 1's as its values. Keeping it as it is would lead the algorithm to think 0 is lower value and 1 is a higher value, which should not be the case since the gender cannot be ordinal feature.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "wDII7RbTbFmM"
   },
   "outputs": [],
   "source": [
    "dataset = pd.get_dummies(df, columns=['sex', 'cp', 'fbs', 'restecg', 'exang', 'slope', 'ca', 'thal'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "-Eba0WwwclFj"
   },
   "source": [
    "## Feature Scaling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 123
    },
    "colab_type": "code",
    "id": "szazUF3JfGiC",
    "outputId": "d0186392-77bd-4dfd-8a40-5c6760e1a76b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['age', 'trestbps', 'chol', 'thalach', 'oldpeak', 'target', 'sex_0',\n",
       "       'sex_1', 'cp_0', 'cp_1', 'cp_2', 'cp_3', 'fbs_0', 'fbs_1', 'restecg_0',\n",
       "       'restecg_1', 'restecg_2', 'exang_0', 'exang_1', 'slope_0', 'slope_1',\n",
       "       'slope_2', 'ca_0', 'ca_1', 'ca_2', 'ca_3', 'ca_4', 'thal_0', 'thal_1',\n",
       "       'thal_2', 'thal_3'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "gktjo1Gye6Ra"
   },
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "standScaler = StandardScaler()\n",
    "columns_to_scale = ['age', 'trestbps', 'chol', 'thalach', 'oldpeak']\n",
    "dataset[columns_to_scale] = standScaler.fit_transform(dataset[columns_to_scale])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 217
    },
    "colab_type": "code",
    "id": "1ttukfhofhBT",
    "outputId": "4caa3a99-6007-4679-a69d-7ddfc1376bd1"
   },
   "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>age</th>\n",
       "      <th>trestbps</th>\n",
       "      <th>chol</th>\n",
       "      <th>thalach</th>\n",
       "      <th>oldpeak</th>\n",
       "      <th>target</th>\n",
       "      <th>sex_0</th>\n",
       "      <th>sex_1</th>\n",
       "      <th>cp_0</th>\n",
       "      <th>cp_1</th>\n",
       "      <th>...</th>\n",
       "      <th>slope_2</th>\n",
       "      <th>ca_0</th>\n",
       "      <th>ca_1</th>\n",
       "      <th>ca_2</th>\n",
       "      <th>ca_3</th>\n",
       "      <th>ca_4</th>\n",
       "      <th>thal_0</th>\n",
       "      <th>thal_1</th>\n",
       "      <th>thal_2</th>\n",
       "      <th>thal_3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.952197</td>\n",
       "      <td>0.763956</td>\n",
       "      <td>-0.256334</td>\n",
       "      <td>0.015443</td>\n",
       "      <td>1.087338</td>\n",
       "      <td>1</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>1</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>-1.915313</td>\n",
       "      <td>-0.092738</td>\n",
       "      <td>0.072199</td>\n",
       "      <td>1.633471</td>\n",
       "      <td>2.122573</td>\n",
       "      <td>1</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>1</td>\n",
       "      <td>0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>-1.474158</td>\n",
       "      <td>-0.092738</td>\n",
       "      <td>-0.816773</td>\n",
       "      <td>0.977514</td>\n",
       "      <td>0.310912</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</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",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0.180175</td>\n",
       "      <td>-0.663867</td>\n",
       "      <td>-0.198357</td>\n",
       "      <td>1.239897</td>\n",
       "      <td>-0.206705</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</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",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0.290464</td>\n",
       "      <td>-0.663867</td>\n",
       "      <td>2.082050</td>\n",
       "      <td>0.583939</td>\n",
       "      <td>-0.379244</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</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",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        age  trestbps      chol   thalach   oldpeak  target  sex_0  sex_1  \\\n",
       "0  0.952197  0.763956 -0.256334  0.015443  1.087338       1      0      1   \n",
       "1 -1.915313 -0.092738  0.072199  1.633471  2.122573       1      0      1   \n",
       "2 -1.474158 -0.092738 -0.816773  0.977514  0.310912       1      1      0   \n",
       "3  0.180175 -0.663867 -0.198357  1.239897 -0.206705       1      0      1   \n",
       "4  0.290464 -0.663867  2.082050  0.583939 -0.379244       1      1      0   \n",
       "\n",
       "   cp_0  cp_1  ...  slope_2  ca_0  ca_1  ca_2  ca_3  ca_4  thal_0  thal_1  \\\n",
       "0     0     0  ...        0     1     0     0     0     0       0       1   \n",
       "1     0     0  ...        0     1     0     0     0     0       0       0   \n",
       "2     0     1  ...        1     1     0     0     0     0       0       0   \n",
       "3     0     1  ...        1     1     0     0     0     0       0       0   \n",
       "4     1     0  ...        1     1     0     0     0     0       0       0   \n",
       "\n",
       "   thal_2  thal_3  \n",
       "0       0       0  \n",
       "1       1       0  \n",
       "2       1       0  \n",
       "3       1       0  \n",
       "4       1       0  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "ordVXCj7gMwb"
   },
   "outputs": [],
   "source": [
    "# Splitting the dataset into dependent and independent features\n",
    "X = dataset.drop('target', axis=1)\n",
    "y = dataset['target']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "bm53VwAcgnUa"
   },
   "source": [
    "# **Model Building**\n",
    "\n",
    "I will be experimenting with 3 algorithms:\n",
    "1. KNeighbors Classifier\n",
    "2. Decision Tree Classifier\n",
    "3. Random Forest Classifier"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "eko0NbkMg_rA"
   },
   "source": [
    "## KNeighbors Classifier Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "lW11vJprg7gd"
   },
   "outputs": [],
   "source": [
    "# Importing essential libraries\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.model_selection import cross_val_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "4m-Bsa2vhqV_"
   },
   "outputs": [],
   "source": [
    "# Finding the best accuracy for knn algorithm using cross_val_score \n",
    "knn_scores = []\n",
    "for i in range(1, 21):\n",
    "  knn_classifier = KNeighborsClassifier(n_neighbors=i)\n",
    "  cvs_scores = cross_val_score(knn_classifier, X, y, cv=10)\n",
    "  knn_scores.append(round(cvs_scores.mean(),3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 850
    },
    "colab_type": "code",
    "id": "N5jcGJwZhqSm",
    "outputId": "e1cd2c46-ddba-4cab-b44b-4350ff5a87ec"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'K Neighbors Classifier scores for different K values')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the results of knn_scores\n",
    "plt.figure(figsize=(20,15))\n",
    "plt.plot([k for k in range(1, 21)], knn_scores, color = 'red')\n",
    "for i in range(1,21):\n",
    "    plt.text(i, knn_scores[i-1], (i, knn_scores[i-1]))\n",
    "plt.xticks([i for i in range(1, 21)])\n",
    "plt.xlabel('Number of Neighbors (K)')\n",
    "plt.ylabel('Scores')\n",
    "plt.title('K Neighbors Classifier scores for different K values')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "RHXct12JhqM1",
    "outputId": "7cd5fe61-f4bd-430d-b270-2455f246a009"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "KNeighbours Classifier Accuracy with K=12 is: 85.07000000000001%\n"
     ]
    }
   ],
   "source": [
    "# Training the knn classifier model with k value as 12\n",
    "knn_classifier = KNeighborsClassifier(n_neighbors=12)\n",
    "cvs_scores = cross_val_score(knn_classifier, X, y, cv=10)\n",
    "print(\"KNeighbours Classifier Accuracy with K=12 is: {}%\".format(round(cvs_scores.mean(), 4)*100))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "ePRTeaPJhD8i"
   },
   "source": [
    "## Decision Tree Classifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "qaRq7M9fnYcy"
   },
   "outputs": [],
   "source": [
    "# Importing essential libraries\n",
    "from sklearn.tree import DecisionTreeClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "g2hdbvoDuVaC"
   },
   "outputs": [],
   "source": [
    "# Finding the best accuracy for decision tree algorithm using cross_val_score \n",
    "decision_scores = []\n",
    "for i in range(1, 11):\n",
    "  decision_classifier = DecisionTreeClassifier(max_depth=i)\n",
    "  cvs_scores = cross_val_score(decision_classifier, X, y, cv=10)\n",
    "  decision_scores.append(round(cvs_scores.mean(),3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 850
    },
    "colab_type": "code",
    "id": "JKko_7FUuVW1",
    "outputId": "739c5292-7f32-4260-8623-725ac63870af"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Decision Tree Classifier scores for different depth values')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the results of decision_scores\n",
    "plt.figure(figsize=(20,15))\n",
    "plt.plot([i for i in range(1, 11)], decision_scores, color = 'red')\n",
    "for i in range(1,11):\n",
    "    plt.text(i, decision_scores[i-1], (i, decision_scores[i-1]))\n",
    "plt.xticks([i for i in range(1, 11)])\n",
    "plt.xlabel('Depth of Decision Tree (N)')\n",
    "plt.ylabel('Scores')\n",
    "plt.title('Decision Tree Classifier scores for different depth values')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "rzELpIXKuVJZ",
    "outputId": "df5f719d-ee67-4acc-9d90-1212c98b631a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decision Tree Classifier Accuracy with max_depth=3 is: 78.77%\n"
     ]
    }
   ],
   "source": [
    "# Training the decision tree classifier model with max_depth value as 3\n",
    "decision_classifier = DecisionTreeClassifier(max_depth=3)\n",
    "cvs_scores = cross_val_score(decision_classifier, X, y, cv=10)\n",
    "print(\"Decision Tree Classifier Accuracy with max_depth=3 is: {}%\".format(round(cvs_scores.mean(), 4)*100))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "4zX2_2gmhI0r"
   },
   "source": [
    "## Random Forest Classifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "m0XtdrqKk2Vz"
   },
   "outputs": [],
   "source": [
    "# Importing essential libraries\n",
    "from sklearn.ensemble import RandomForestClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "9wMZ1NOplNjJ"
   },
   "outputs": [],
   "source": [
    "# Finding the best accuracy for random forest algorithm using cross_val_score \n",
    "forest_scores = []\n",
    "for i in range(10, 101, 10):\n",
    "  forest_classifier = RandomForestClassifier(n_estimators=i)\n",
    "  cvs_scores = cross_val_score(forest_classifier, X, y, cv=5)\n",
    "  forest_scores.append(round(cvs_scores.mean(),3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 841
    },
    "colab_type": "code",
    "id": "qlhqwMXkljap",
    "outputId": "626286a8-72b9-4da5-ab34-5d8343b83382"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Random Forest Classifier scores for different N values')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting the results of forest_scores\n",
    "plt.figure(figsize=(20,15))\n",
    "plt.plot([n for n in range(10, 101, 10)], forest_scores, color = 'red')\n",
    "for i in range(1,11):\n",
    "    plt.text(i*10, forest_scores[i-1], (i*10, forest_scores[i-1]))\n",
    "plt.xticks([i for i in range(10, 101, 10)])\n",
    "plt.xlabel('Number of Estimators (N)')\n",
    "plt.ylabel('Scores')\n",
    "plt.title('Random Forest Classifier scores for different N values')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 34
    },
    "colab_type": "code",
    "id": "FERYFAEgmdBx",
    "outputId": "063bbb32-59f6-4c9e-d971-e43504c7a87a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Random Forest Classifier Accuracy with n_estimators=90 is: 83.82%\n"
     ]
    }
   ],
   "source": [
    "# Training the random forest classifier model with n value as 90\n",
    "forest_classifier = RandomForestClassifier(n_estimators=90)\n",
    "cvs_scores = cross_val_score(forest_classifier, X, y, cv=5)\n",
    "print(\"Random Forest Classifier Accuracy with n_estimators=90 is: {}%\".format(round(cvs_scores.mean(), 4)*100))"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [
    "9BEBuDSiTwfU",
    "cVlUJwidVjLr"
   ],
   "name": "Heart Disease Prediction.ipynb",
   "provenance": [],
   "toc_visible": true
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}