Diagnosis_of_Parkinson's_Disease_.ipynb

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      "cell_type": "markdown",
      "source": [
        "**Introduction to SVM**\n",
        "\n",
        "Use SVM to build and train a model using human symptoms record, and classify cells to whether the symptoms shows Parkinson's Positive or Negative\n",
        "\n",
        "SVM works by mapping data to a high-dimensional feature space so that data points can be categorized, even when the data are not otherwise linearly seperable (This gets done by Kernel function of SVM Classifier). \n",
        "\n",
        "A seperator between the categories is found, then the data is transformed in such a way that the seperator could be drawn as a hyperplane\n",
        "\n"
      ],
      "metadata": {
        "id": "TE8pglmcaNsl"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Importing The Dependencies"
      ],
      "metadata": {
        "id": "gOEWwv7owvqG"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "mR1_FubUwhZ-"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from sklearn import svm\n",
        "from sklearn.metrics import accuracy_score"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Data collection & analysis"
      ],
      "metadata": {
        "id": "qh7Nr--Y3uvX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# loading the data from csv file to a Pandas dataframe\n",
        "parkinsons_data=pd.read_csv('/content/parkinsons.csv')"
      ],
      "metadata": {
        "id": "WduAbV-Z3zh_"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# printing the first 10 rows of the dataframe\n",
        "parkinsons_data.head(10)"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 456
        },
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        "outputId": "bc4185f4-3517-485a-e810-44bca8a51f4a"
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      "execution_count": 12,
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              "             name  MDVP:Fo(Hz)  MDVP:Fhi(Hz)  MDVP:Flo(Hz)  MDVP:Jitter(%)  \\\n",
              "0  phon_R01_S01_1      119.992       157.302        74.997         0.00784   \n",
              "1  phon_R01_S01_2      122.400       148.650       113.819         0.00968   \n",
              "2  phon_R01_S01_3      116.682       131.111       111.555         0.01050   \n",
              "3  phon_R01_S01_4      116.676       137.871       111.366         0.00997   \n",
              "4  phon_R01_S01_5      116.014       141.781       110.655         0.01284   \n",
              "5  phon_R01_S01_6      120.552       131.162       113.787         0.00968   \n",
              "6  phon_R01_S02_1      120.267       137.244       114.820         0.00333   \n",
              "7  phon_R01_S02_2      107.332       113.840       104.315         0.00290   \n",
              "8  phon_R01_S02_3       95.730       132.068        91.754         0.00551   \n",
              "9  phon_R01_S02_4       95.056       120.103        91.226         0.00532   \n",
              "\n",
              "   MDVP:Jitter(Abs)  MDVP:RAP  MDVP:PPQ  Jitter:DDP  MDVP:Shimmer  ...  \\\n",
              "0           0.00007   0.00370   0.00554     0.01109       0.04374  ...   \n",
              "1           0.00008   0.00465   0.00696     0.01394       0.06134  ...   \n",
              "2           0.00009   0.00544   0.00781     0.01633       0.05233  ...   \n",
              "3           0.00009   0.00502   0.00698     0.01505       0.05492  ...   \n",
              "4           0.00011   0.00655   0.00908     0.01966       0.06425  ...   \n",
              "5           0.00008   0.00463   0.00750     0.01388       0.04701  ...   \n",
              "6           0.00003   0.00155   0.00202     0.00466       0.01608  ...   \n",
              "7           0.00003   0.00144   0.00182     0.00431       0.01567  ...   \n",
              "8           0.00006   0.00293   0.00332     0.00880       0.02093  ...   \n",
              "9           0.00006   0.00268   0.00332     0.00803       0.02838  ...   \n",
              "\n",
              "   Shimmer:DDA      NHR     HNR  status      RPDE       DFA   spread1  \\\n",
              "0      0.06545  0.02211  21.033       1  0.414783  0.815285 -4.813031   \n",
              "1      0.09403  0.01929  19.085       1  0.458359  0.819521 -4.075192   \n",
              "2      0.08270  0.01309  20.651       1  0.429895  0.825288 -4.443179   \n",
              "3      0.08771  0.01353  20.644       1  0.434969  0.819235 -4.117501   \n",
              "4      0.10470  0.01767  19.649       1  0.417356  0.823484 -3.747787   \n",
              "5      0.06985  0.01222  21.378       1  0.415564  0.825069 -4.242867   \n",
              "6      0.02337  0.00607  24.886       1  0.596040  0.764112 -5.634322   \n",
              "7      0.02487  0.00344  26.892       1  0.637420  0.763262 -6.167603   \n",
              "8      0.03218  0.01070  21.812       1  0.615551  0.773587 -5.498678   \n",
              "9      0.04324  0.01022  21.862       1  0.547037  0.798463 -5.011879   \n",
              "\n",
              "    spread2        D2       PPE  \n",
              "0  0.266482  2.301442  0.284654  \n",
              "1  0.335590  2.486855  0.368674  \n",
              "2  0.311173  2.342259  0.332634  \n",
              "3  0.334147  2.405554  0.368975  \n",
              "4  0.234513  2.332180  0.410335  \n",
              "5  0.299111  2.187560  0.357775  \n",
              "6  0.257682  1.854785  0.211756  \n",
              "7  0.183721  2.064693  0.163755  \n",
              "8  0.327769  2.322511  0.231571  \n",
              "9  0.325996  2.432792  0.271362  \n",
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              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>MDVP:Fo(Hz)</th>\n",
              "      <th>MDVP:Fhi(Hz)</th>\n",
              "      <th>MDVP:Flo(Hz)</th>\n",
              "      <th>MDVP:Jitter(%)</th>\n",
              "      <th>MDVP:Jitter(Abs)</th>\n",
              "      <th>MDVP:RAP</th>\n",
              "      <th>MDVP:PPQ</th>\n",
              "      <th>Jitter:DDP</th>\n",
              "      <th>MDVP:Shimmer</th>\n",
              "      <th>...</th>\n",
              "      <th>Shimmer:DDA</th>\n",
              "      <th>NHR</th>\n",
              "      <th>HNR</th>\n",
              "      <th>status</th>\n",
              "      <th>RPDE</th>\n",
              "      <th>DFA</th>\n",
              "      <th>spread1</th>\n",
              "      <th>spread2</th>\n",
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              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>phon_R01_S01_1</td>\n",
              "      <td>119.992</td>\n",
              "      <td>157.302</td>\n",
              "      <td>74.997</td>\n",
              "      <td>0.00784</td>\n",
              "      <td>0.00007</td>\n",
              "      <td>0.00370</td>\n",
              "      <td>0.00554</td>\n",
              "      <td>0.01109</td>\n",
              "      <td>0.04374</td>\n",
              "      <td>...</td>\n",
              "      <td>0.06545</td>\n",
              "      <td>0.02211</td>\n",
              "      <td>21.033</td>\n",
              "      <td>1</td>\n",
              "      <td>0.414783</td>\n",
              "      <td>0.815285</td>\n",
              "      <td>-4.813031</td>\n",
              "      <td>0.266482</td>\n",
              "      <td>2.301442</td>\n",
              "      <td>0.284654</td>\n",
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              "      <th>1</th>\n",
              "      <td>phon_R01_S01_2</td>\n",
              "      <td>122.400</td>\n",
              "      <td>148.650</td>\n",
              "      <td>113.819</td>\n",
              "      <td>0.00968</td>\n",
              "      <td>0.00008</td>\n",
              "      <td>0.00465</td>\n",
              "      <td>0.00696</td>\n",
              "      <td>0.01394</td>\n",
              "      <td>0.06134</td>\n",
              "      <td>...</td>\n",
              "      <td>0.09403</td>\n",
              "      <td>0.01929</td>\n",
              "      <td>19.085</td>\n",
              "      <td>1</td>\n",
              "      <td>0.458359</td>\n",
              "      <td>0.819521</td>\n",
              "      <td>-4.075192</td>\n",
              "      <td>0.335590</td>\n",
              "      <td>2.486855</td>\n",
              "      <td>0.368674</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>phon_R01_S01_3</td>\n",
              "      <td>116.682</td>\n",
              "      <td>131.111</td>\n",
              "      <td>111.555</td>\n",
              "      <td>0.01050</td>\n",
              "      <td>0.00009</td>\n",
              "      <td>0.00544</td>\n",
              "      <td>0.00781</td>\n",
              "      <td>0.01633</td>\n",
              "      <td>0.05233</td>\n",
              "      <td>...</td>\n",
              "      <td>0.08270</td>\n",
              "      <td>0.01309</td>\n",
              "      <td>20.651</td>\n",
              "      <td>1</td>\n",
              "      <td>0.429895</td>\n",
              "      <td>0.825288</td>\n",
              "      <td>-4.443179</td>\n",
              "      <td>0.311173</td>\n",
              "      <td>2.342259</td>\n",
              "      <td>0.332634</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>phon_R01_S01_4</td>\n",
              "      <td>116.676</td>\n",
              "      <td>137.871</td>\n",
              "      <td>111.366</td>\n",
              "      <td>0.00997</td>\n",
              "      <td>0.00009</td>\n",
              "      <td>0.00502</td>\n",
              "      <td>0.00698</td>\n",
              "      <td>0.01505</td>\n",
              "      <td>0.05492</td>\n",
              "      <td>...</td>\n",
              "      <td>0.08771</td>\n",
              "      <td>0.01353</td>\n",
              "      <td>20.644</td>\n",
              "      <td>1</td>\n",
              "      <td>0.434969</td>\n",
              "      <td>0.819235</td>\n",
              "      <td>-4.117501</td>\n",
              "      <td>0.334147</td>\n",
              "      <td>2.405554</td>\n",
              "      <td>0.368975</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>phon_R01_S01_5</td>\n",
              "      <td>116.014</td>\n",
              "      <td>141.781</td>\n",
              "      <td>110.655</td>\n",
              "      <td>0.01284</td>\n",
              "      <td>0.00011</td>\n",
              "      <td>0.00655</td>\n",
              "      <td>0.00908</td>\n",
              "      <td>0.01966</td>\n",
              "      <td>0.06425</td>\n",
              "      <td>...</td>\n",
              "      <td>0.10470</td>\n",
              "      <td>0.01767</td>\n",
              "      <td>19.649</td>\n",
              "      <td>1</td>\n",
              "      <td>0.417356</td>\n",
              "      <td>0.823484</td>\n",
              "      <td>-3.747787</td>\n",
              "      <td>0.234513</td>\n",
              "      <td>2.332180</td>\n",
              "      <td>0.410335</td>\n",
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              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>phon_R01_S01_6</td>\n",
              "      <td>120.552</td>\n",
              "      <td>131.162</td>\n",
              "      <td>113.787</td>\n",
              "      <td>0.00968</td>\n",
              "      <td>0.00008</td>\n",
              "      <td>0.00463</td>\n",
              "      <td>0.00750</td>\n",
              "      <td>0.01388</td>\n",
              "      <td>0.04701</td>\n",
              "      <td>...</td>\n",
              "      <td>0.06985</td>\n",
              "      <td>0.01222</td>\n",
              "      <td>21.378</td>\n",
              "      <td>1</td>\n",
              "      <td>0.415564</td>\n",
              "      <td>0.825069</td>\n",
              "      <td>-4.242867</td>\n",
              "      <td>0.299111</td>\n",
              "      <td>2.187560</td>\n",
              "      <td>0.357775</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>phon_R01_S02_1</td>\n",
              "      <td>120.267</td>\n",
              "      <td>137.244</td>\n",
              "      <td>114.820</td>\n",
              "      <td>0.00333</td>\n",
              "      <td>0.00003</td>\n",
              "      <td>0.00155</td>\n",
              "      <td>0.00202</td>\n",
              "      <td>0.00466</td>\n",
              "      <td>0.01608</td>\n",
              "      <td>...</td>\n",
              "      <td>0.02337</td>\n",
              "      <td>0.00607</td>\n",
              "      <td>24.886</td>\n",
              "      <td>1</td>\n",
              "      <td>0.596040</td>\n",
              "      <td>0.764112</td>\n",
              "      <td>-5.634322</td>\n",
              "      <td>0.257682</td>\n",
              "      <td>1.854785</td>\n",
              "      <td>0.211756</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>phon_R01_S02_2</td>\n",
              "      <td>107.332</td>\n",
              "      <td>113.840</td>\n",
              "      <td>104.315</td>\n",
              "      <td>0.00290</td>\n",
              "      <td>0.00003</td>\n",
              "      <td>0.00144</td>\n",
              "      <td>0.00182</td>\n",
              "      <td>0.00431</td>\n",
              "      <td>0.01567</td>\n",
              "      <td>...</td>\n",
              "      <td>0.02487</td>\n",
              "      <td>0.00344</td>\n",
              "      <td>26.892</td>\n",
              "      <td>1</td>\n",
              "      <td>0.637420</td>\n",
              "      <td>0.763262</td>\n",
              "      <td>-6.167603</td>\n",
              "      <td>0.183721</td>\n",
              "      <td>2.064693</td>\n",
              "      <td>0.163755</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>phon_R01_S02_3</td>\n",
              "      <td>95.730</td>\n",
              "      <td>132.068</td>\n",
              "      <td>91.754</td>\n",
              "      <td>0.00551</td>\n",
              "      <td>0.00006</td>\n",
              "      <td>0.00293</td>\n",
              "      <td>0.00332</td>\n",
              "      <td>0.00880</td>\n",
              "      <td>0.02093</td>\n",
              "      <td>...</td>\n",
              "      <td>0.03218</td>\n",
              "      <td>0.01070</td>\n",
              "      <td>21.812</td>\n",
              "      <td>1</td>\n",
              "      <td>0.615551</td>\n",
              "      <td>0.773587</td>\n",
              "      <td>-5.498678</td>\n",
              "      <td>0.327769</td>\n",
              "      <td>2.322511</td>\n",
              "      <td>0.231571</td>\n",
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              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>phon_R01_S02_4</td>\n",
              "      <td>95.056</td>\n",
              "      <td>120.103</td>\n",
              "      <td>91.226</td>\n",
              "      <td>0.00532</td>\n",
              "      <td>0.00006</td>\n",
              "      <td>0.00268</td>\n",
              "      <td>0.00332</td>\n",
              "      <td>0.00803</td>\n",
              "      <td>0.02838</td>\n",
              "      <td>...</td>\n",
              "      <td>0.04324</td>\n",
              "      <td>0.01022</td>\n",
              "      <td>21.862</td>\n",
              "      <td>1</td>\n",
              "      <td>0.547037</td>\n",
              "      <td>0.798463</td>\n",
              "      <td>-5.011879</td>\n",
              "      <td>0.325996</td>\n",
              "      <td>2.432792</td>\n",
              "      <td>0.271362</td>\n",
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              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-c091eaf8-f971-49b1-9d6a-71a484b88d0b button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c091eaf8-f971-49b1-9d6a-71a484b88d0b');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#printing the first 5 rows of data\n",
        "parkinsons_data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299
        },
        "id": "moc6NUeg5EOM",
        "outputId": "e5c22321-16c9-4ddb-9705-553b81c5397b"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             name  MDVP:Fo(Hz)  MDVP:Fhi(Hz)  MDVP:Flo(Hz)  MDVP:Jitter(%)  \\\n",
              "0  phon_R01_S01_1      119.992       157.302        74.997         0.00784   \n",
              "1  phon_R01_S01_2      122.400       148.650       113.819         0.00968   \n",
              "2  phon_R01_S01_3      116.682       131.111       111.555         0.01050   \n",
              "3  phon_R01_S01_4      116.676       137.871       111.366         0.00997   \n",
              "4  phon_R01_S01_5      116.014       141.781       110.655         0.01284   \n",
              "\n",
              "   MDVP:Jitter(Abs)  MDVP:RAP  MDVP:PPQ  Jitter:DDP  MDVP:Shimmer  ...  \\\n",
              "0           0.00007   0.00370   0.00554     0.01109       0.04374  ...   \n",
              "1           0.00008   0.00465   0.00696     0.01394       0.06134  ...   \n",
              "2           0.00009   0.00544   0.00781     0.01633       0.05233  ...   \n",
              "3           0.00009   0.00502   0.00698     0.01505       0.05492  ...   \n",
              "4           0.00011   0.00655   0.00908     0.01966       0.06425  ...   \n",
              "\n",
              "   Shimmer:DDA      NHR     HNR  status      RPDE       DFA   spread1  \\\n",
              "0      0.06545  0.02211  21.033       1  0.414783  0.815285 -4.813031   \n",
              "1      0.09403  0.01929  19.085       1  0.458359  0.819521 -4.075192   \n",
              "2      0.08270  0.01309  20.651       1  0.429895  0.825288 -4.443179   \n",
              "3      0.08771  0.01353  20.644       1  0.434969  0.819235 -4.117501   \n",
              "4      0.10470  0.01767  19.649       1  0.417356  0.823484 -3.747787   \n",
              "\n",
              "    spread2        D2       PPE  \n",
              "0  0.266482  2.301442  0.284654  \n",
              "1  0.335590  2.486855  0.368674  \n",
              "2  0.311173  2.342259  0.332634  \n",
              "3  0.334147  2.405554  0.368975  \n",
              "4  0.234513  2.332180  0.410335  \n",
              "\n",
              "[5 rows x 24 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-2133a220-ec49-4c60-a0ef-a347255a9524\">\n",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
              "      <th>MDVP:Fo(Hz)</th>\n",
              "      <th>MDVP:Fhi(Hz)</th>\n",
              "      <th>MDVP:Flo(Hz)</th>\n",
              "      <th>MDVP:Jitter(%)</th>\n",
              "      <th>MDVP:Jitter(Abs)</th>\n",
              "      <th>MDVP:RAP</th>\n",
              "      <th>MDVP:PPQ</th>\n",
              "      <th>Jitter:DDP</th>\n",
              "      <th>MDVP:Shimmer</th>\n",
              "      <th>...</th>\n",
              "      <th>Shimmer:DDA</th>\n",
              "      <th>NHR</th>\n",
              "      <th>HNR</th>\n",
              "      <th>status</th>\n",
              "      <th>RPDE</th>\n",
              "      <th>DFA</th>\n",
              "      <th>spread1</th>\n",
              "      <th>spread2</th>\n",
              "      <th>D2</th>\n",
              "      <th>PPE</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>phon_R01_S01_1</td>\n",
              "      <td>119.992</td>\n",
              "      <td>157.302</td>\n",
              "      <td>74.997</td>\n",
              "      <td>0.00784</td>\n",
              "      <td>0.00007</td>\n",
              "      <td>0.00370</td>\n",
              "      <td>0.00554</td>\n",
              "      <td>0.01109</td>\n",
              "      <td>0.04374</td>\n",
              "      <td>...</td>\n",
              "      <td>0.06545</td>\n",
              "      <td>0.02211</td>\n",
              "      <td>21.033</td>\n",
              "      <td>1</td>\n",
              "      <td>0.414783</td>\n",
              "      <td>0.815285</td>\n",
              "      <td>-4.813031</td>\n",
              "      <td>0.266482</td>\n",
              "      <td>2.301442</td>\n",
              "      <td>0.284654</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>phon_R01_S01_2</td>\n",
              "      <td>122.400</td>\n",
              "      <td>148.650</td>\n",
              "      <td>113.819</td>\n",
              "      <td>0.00968</td>\n",
              "      <td>0.00008</td>\n",
              "      <td>0.00465</td>\n",
              "      <td>0.00696</td>\n",
              "      <td>0.01394</td>\n",
              "      <td>0.06134</td>\n",
              "      <td>...</td>\n",
              "      <td>0.09403</td>\n",
              "      <td>0.01929</td>\n",
              "      <td>19.085</td>\n",
              "      <td>1</td>\n",
              "      <td>0.458359</td>\n",
              "      <td>0.819521</td>\n",
              "      <td>-4.075192</td>\n",
              "      <td>0.335590</td>\n",
              "      <td>2.486855</td>\n",
              "      <td>0.368674</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>phon_R01_S01_3</td>\n",
              "      <td>116.682</td>\n",
              "      <td>131.111</td>\n",
              "      <td>111.555</td>\n",
              "      <td>0.01050</td>\n",
              "      <td>0.00009</td>\n",
              "      <td>0.00544</td>\n",
              "      <td>0.00781</td>\n",
              "      <td>0.01633</td>\n",
              "      <td>0.05233</td>\n",
              "      <td>...</td>\n",
              "      <td>0.08270</td>\n",
              "      <td>0.01309</td>\n",
              "      <td>20.651</td>\n",
              "      <td>1</td>\n",
              "      <td>0.429895</td>\n",
              "      <td>0.825288</td>\n",
              "      <td>-4.443179</td>\n",
              "      <td>0.311173</td>\n",
              "      <td>2.342259</td>\n",
              "      <td>0.332634</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>phon_R01_S01_4</td>\n",
              "      <td>116.676</td>\n",
              "      <td>137.871</td>\n",
              "      <td>111.366</td>\n",
              "      <td>0.00997</td>\n",
              "      <td>0.00009</td>\n",
              "      <td>0.00502</td>\n",
              "      <td>0.00698</td>\n",
              "      <td>0.01505</td>\n",
              "      <td>0.05492</td>\n",
              "      <td>...</td>\n",
              "      <td>0.08771</td>\n",
              "      <td>0.01353</td>\n",
              "      <td>20.644</td>\n",
              "      <td>1</td>\n",
              "      <td>0.434969</td>\n",
              "      <td>0.819235</td>\n",
              "      <td>-4.117501</td>\n",
              "      <td>0.334147</td>\n",
              "      <td>2.405554</td>\n",
              "      <td>0.368975</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>phon_R01_S01_5</td>\n",
              "      <td>116.014</td>\n",
              "      <td>141.781</td>\n",
              "      <td>110.655</td>\n",
              "      <td>0.01284</td>\n",
              "      <td>0.00011</td>\n",
              "      <td>0.00655</td>\n",
              "      <td>0.00908</td>\n",
              "      <td>0.01966</td>\n",
              "      <td>0.06425</td>\n",
              "      <td>...</td>\n",
              "      <td>0.10470</td>\n",
              "      <td>0.01767</td>\n",
              "      <td>19.649</td>\n",
              "      <td>1</td>\n",
              "      <td>0.417356</td>\n",
              "      <td>0.823484</td>\n",
              "      <td>-3.747787</td>\n",
              "      <td>0.234513</td>\n",
              "      <td>2.332180</td>\n",
              "      <td>0.410335</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 24 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2133a220-ec49-4c60-a0ef-a347255a9524')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  <style>\n",
              "    .colab-df-container {\n",
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              "    .colab-df-convert {\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-2133a220-ec49-4c60-a0ef-a347255a9524');\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#number of rows and columns in the dataframe\n",
        "parkinsons_data.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EWNnfgoa5Rrd",
        "outputId": "9ebafd0f-6e2f-4420-8213-21f02f0251ab"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(195, 24)"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#getting more information about the dataset\n",
        "parkinsons_data.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OVgYekGV5ra0",
        "outputId": "b3e1ea81-0fbb-4205-9f13-9f7ddb2f95d8"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 195 entries, 0 to 194\n",
            "Data columns (total 24 columns):\n",
            " #   Column            Non-Null Count  Dtype  \n",
            "---  ------            --------------  -----  \n",
            " 0   name              195 non-null    object \n",
            " 1   MDVP:Fo(Hz)       195 non-null    float64\n",
            " 2   MDVP:Fhi(Hz)      195 non-null    float64\n",
            " 3   MDVP:Flo(Hz)      195 non-null    float64\n",
            " 4   MDVP:Jitter(%)    195 non-null    float64\n",
            " 5   MDVP:Jitter(Abs)  195 non-null    float64\n",
            " 6   MDVP:RAP          195 non-null    float64\n",
            " 7   MDVP:PPQ          195 non-null    float64\n",
            " 8   Jitter:DDP        195 non-null    float64\n",
            " 9   MDVP:Shimmer      195 non-null    float64\n",
            " 10  MDVP:Shimmer(dB)  195 non-null    float64\n",
            " 11  Shimmer:APQ3      195 non-null    float64\n",
            " 12  Shimmer:APQ5      195 non-null    float64\n",
            " 13  MDVP:APQ          195 non-null    float64\n",
            " 14  Shimmer:DDA       195 non-null    float64\n",
            " 15  NHR               195 non-null    float64\n",
            " 16  HNR               195 non-null    float64\n",
            " 17  status            195 non-null    int64  \n",
            " 18  RPDE              195 non-null    float64\n",
            " 19  DFA               195 non-null    float64\n",
            " 20  spread1           195 non-null    float64\n",
            " 21  spread2           195 non-null    float64\n",
            " 22  D2                195 non-null    float64\n",
            " 23  PPE               195 non-null    float64\n",
            "dtypes: float64(22), int64(1), object(1)\n",
            "memory usage: 36.7+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#checking for missing values in each column\n",
        "parkinsons_data.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3Ql3JEnU55-T",
        "outputId": "032c58f7-499d-4309-d8ac-2e30541f3533"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name                0\n",
              "MDVP:Fo(Hz)         0\n",
              "MDVP:Fhi(Hz)        0\n",
              "MDVP:Flo(Hz)        0\n",
              "MDVP:Jitter(%)      0\n",
              "MDVP:Jitter(Abs)    0\n",
              "MDVP:RAP            0\n",
              "MDVP:PPQ            0\n",
              "Jitter:DDP          0\n",
              "MDVP:Shimmer        0\n",
              "MDVP:Shimmer(dB)    0\n",
              "Shimmer:APQ3        0\n",
              "Shimmer:APQ5        0\n",
              "MDVP:APQ            0\n",
              "Shimmer:DDA         0\n",
              "NHR                 0\n",
              "HNR                 0\n",
              "status              0\n",
              "RPDE                0\n",
              "DFA                 0\n",
              "spread1             0\n",
              "spread2             0\n",
              "D2                  0\n",
              "PPE                 0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# getting some statistical measures about the data\n",
        "parkinsons_data.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "id": "LpCSM4606NDZ",
        "outputId": "56345292-4543-405b-c7ae-a6847fe1cd15"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       MDVP:Fo(Hz)  MDVP:Fhi(Hz)  MDVP:Flo(Hz)  MDVP:Jitter(%)  \\\n",
              "count   195.000000    195.000000    195.000000      195.000000   \n",
              "mean    154.228641    197.104918    116.324631        0.006220   \n",
              "std      41.390065     91.491548     43.521413        0.004848   \n",
              "min      88.333000    102.145000     65.476000        0.001680   \n",
              "25%     117.572000    134.862500     84.291000        0.003460   \n",
              "50%     148.790000    175.829000    104.315000        0.004940   \n",
              "75%     182.769000    224.205500    140.018500        0.007365   \n",
              "max     260.105000    592.030000    239.170000        0.033160   \n",
              "\n",
              "       MDVP:Jitter(Abs)    MDVP:RAP    MDVP:PPQ  Jitter:DDP  MDVP:Shimmer  \\\n",
              "count        195.000000  195.000000  195.000000  195.000000    195.000000   \n",
              "mean           0.000044    0.003306    0.003446    0.009920      0.029709   \n",
              "std            0.000035    0.002968    0.002759    0.008903      0.018857   \n",
              "min            0.000007    0.000680    0.000920    0.002040      0.009540   \n",
              "25%            0.000020    0.001660    0.001860    0.004985      0.016505   \n",
              "50%            0.000030    0.002500    0.002690    0.007490      0.022970   \n",
              "75%            0.000060    0.003835    0.003955    0.011505      0.037885   \n",
              "max            0.000260    0.021440    0.019580    0.064330      0.119080   \n",
              "\n",
              "       MDVP:Shimmer(dB)  ...  Shimmer:DDA         NHR         HNR      status  \\\n",
              "count        195.000000  ...   195.000000  195.000000  195.000000  195.000000   \n",
              "mean           0.282251  ...     0.046993    0.024847   21.885974    0.753846   \n",
              "std            0.194877  ...     0.030459    0.040418    4.425764    0.431878   \n",
              "min            0.085000  ...     0.013640    0.000650    8.441000    0.000000   \n",
              "25%            0.148500  ...     0.024735    0.005925   19.198000    1.000000   \n",
              "50%            0.221000  ...     0.038360    0.011660   22.085000    1.000000   \n",
              "75%            0.350000  ...     0.060795    0.025640   25.075500    1.000000   \n",
              "max            1.302000  ...     0.169420    0.314820   33.047000    1.000000   \n",
              "\n",
              "             RPDE         DFA     spread1     spread2          D2         PPE  \n",
              "count  195.000000  195.000000  195.000000  195.000000  195.000000  195.000000  \n",
              "mean     0.498536    0.718099   -5.684397    0.226510    2.381826    0.206552  \n",
              "std      0.103942    0.055336    1.090208    0.083406    0.382799    0.090119  \n",
              "min      0.256570    0.574282   -7.964984    0.006274    1.423287    0.044539  \n",
              "25%      0.421306    0.674758   -6.450096    0.174351    2.099125    0.137451  \n",
              "50%      0.495954    0.722254   -5.720868    0.218885    2.361532    0.194052  \n",
              "75%      0.587562    0.761881   -5.046192    0.279234    2.636456    0.252980  \n",
              "max      0.685151    0.825288   -2.434031    0.450493    3.671155    0.527367  \n",
              "\n",
              "[8 rows x 23 columns]"
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              "      <th></th>\n",
              "      <th>MDVP:Fo(Hz)</th>\n",
              "      <th>MDVP:Fhi(Hz)</th>\n",
              "      <th>MDVP:Flo(Hz)</th>\n",
              "      <th>MDVP:Jitter(%)</th>\n",
              "      <th>MDVP:Jitter(Abs)</th>\n",
              "      <th>MDVP:RAP</th>\n",
              "      <th>MDVP:PPQ</th>\n",
              "      <th>Jitter:DDP</th>\n",
              "      <th>MDVP:Shimmer</th>\n",
              "      <th>MDVP:Shimmer(dB)</th>\n",
              "      <th>...</th>\n",
              "      <th>Shimmer:DDA</th>\n",
              "      <th>NHR</th>\n",
              "      <th>HNR</th>\n",
              "      <th>status</th>\n",
              "      <th>RPDE</th>\n",
              "      <th>DFA</th>\n",
              "      <th>spread1</th>\n",
              "      <th>spread2</th>\n",
              "      <th>D2</th>\n",
              "      <th>PPE</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>195.000000</td>\n",
              "      <td>195.000000</td>\n",
              "      <td>195.000000</td>\n",
              "      <td>195.000000</td>\n",
              "      <td>195.000000</td>\n",
              "      <td>195.000000</td>\n",
              "      <td>195.000000</td>\n",
              "      <td>195.000000</td>\n",
              "      <td>195.000000</td>\n",
              "      <td>195.000000</td>\n",
              "      <td>...</td>\n",
              "      <td>195.000000</td>\n",
              "      <td>195.000000</td>\n",
              "      <td>195.000000</td>\n",
              "      <td>195.000000</td>\n",
              "      <td>195.000000</td>\n",
              "      <td>195.000000</td>\n",
              "      <td>195.000000</td>\n",
              "      <td>195.000000</td>\n",
              "      <td>195.000000</td>\n",
              "      <td>195.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>154.228641</td>\n",
              "      <td>197.104918</td>\n",
              "      <td>116.324631</td>\n",
              "      <td>0.006220</td>\n",
              "      <td>0.000044</td>\n",
              "      <td>0.003306</td>\n",
              "      <td>0.003446</td>\n",
              "      <td>0.009920</td>\n",
              "      <td>0.029709</td>\n",
              "      <td>0.282251</td>\n",
              "      <td>...</td>\n",
              "      <td>0.046993</td>\n",
              "      <td>0.024847</td>\n",
              "      <td>21.885974</td>\n",
              "      <td>0.753846</td>\n",
              "      <td>0.498536</td>\n",
              "      <td>0.718099</td>\n",
              "      <td>-5.684397</td>\n",
              "      <td>0.226510</td>\n",
              "      <td>2.381826</td>\n",
              "      <td>0.206552</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>41.390065</td>\n",
              "      <td>91.491548</td>\n",
              "      <td>43.521413</td>\n",
              "      <td>0.004848</td>\n",
              "      <td>0.000035</td>\n",
              "      <td>0.002968</td>\n",
              "      <td>0.002759</td>\n",
              "      <td>0.008903</td>\n",
              "      <td>0.018857</td>\n",
              "      <td>0.194877</td>\n",
              "      <td>...</td>\n",
              "      <td>0.030459</td>\n",
              "      <td>0.040418</td>\n",
              "      <td>4.425764</td>\n",
              "      <td>0.431878</td>\n",
              "      <td>0.103942</td>\n",
              "      <td>0.055336</td>\n",
              "      <td>1.090208</td>\n",
              "      <td>0.083406</td>\n",
              "      <td>0.382799</td>\n",
              "      <td>0.090119</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>88.333000</td>\n",
              "      <td>102.145000</td>\n",
              "      <td>65.476000</td>\n",
              "      <td>0.001680</td>\n",
              "      <td>0.000007</td>\n",
              "      <td>0.000680</td>\n",
              "      <td>0.000920</td>\n",
              "      <td>0.002040</td>\n",
              "      <td>0.009540</td>\n",
              "      <td>0.085000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.013640</td>\n",
              "      <td>0.000650</td>\n",
              "      <td>8.441000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.256570</td>\n",
              "      <td>0.574282</td>\n",
              "      <td>-7.964984</td>\n",
              "      <td>0.006274</td>\n",
              "      <td>1.423287</td>\n",
              "      <td>0.044539</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>117.572000</td>\n",
              "      <td>134.862500</td>\n",
              "      <td>84.291000</td>\n",
              "      <td>0.003460</td>\n",
              "      <td>0.000020</td>\n",
              "      <td>0.001660</td>\n",
              "      <td>0.001860</td>\n",
              "      <td>0.004985</td>\n",
              "      <td>0.016505</td>\n",
              "      <td>0.148500</td>\n",
              "      <td>...</td>\n",
              "      <td>0.024735</td>\n",
              "      <td>0.005925</td>\n",
              "      <td>19.198000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.421306</td>\n",
              "      <td>0.674758</td>\n",
              "      <td>-6.450096</td>\n",
              "      <td>0.174351</td>\n",
              "      <td>2.099125</td>\n",
              "      <td>0.137451</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>148.790000</td>\n",
              "      <td>175.829000</td>\n",
              "      <td>104.315000</td>\n",
              "      <td>0.004940</td>\n",
              "      <td>0.000030</td>\n",
              "      <td>0.002500</td>\n",
              "      <td>0.002690</td>\n",
              "      <td>0.007490</td>\n",
              "      <td>0.022970</td>\n",
              "      <td>0.221000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.038360</td>\n",
              "      <td>0.011660</td>\n",
              "      <td>22.085000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.495954</td>\n",
              "      <td>0.722254</td>\n",
              "      <td>-5.720868</td>\n",
              "      <td>0.218885</td>\n",
              "      <td>2.361532</td>\n",
              "      <td>0.194052</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>182.769000</td>\n",
              "      <td>224.205500</td>\n",
              "      <td>140.018500</td>\n",
              "      <td>0.007365</td>\n",
              "      <td>0.000060</td>\n",
              "      <td>0.003835</td>\n",
              "      <td>0.003955</td>\n",
              "      <td>0.011505</td>\n",
              "      <td>0.037885</td>\n",
              "      <td>0.350000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.060795</td>\n",
              "      <td>0.025640</td>\n",
              "      <td>25.075500</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.587562</td>\n",
              "      <td>0.761881</td>\n",
              "      <td>-5.046192</td>\n",
              "      <td>0.279234</td>\n",
              "      <td>2.636456</td>\n",
              "      <td>0.252980</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>260.105000</td>\n",
              "      <td>592.030000</td>\n",
              "      <td>239.170000</td>\n",
              "      <td>0.033160</td>\n",
              "      <td>0.000260</td>\n",
              "      <td>0.021440</td>\n",
              "      <td>0.019580</td>\n",
              "      <td>0.064330</td>\n",
              "      <td>0.119080</td>\n",
              "      <td>1.302000</td>\n",
              "      <td>...</td>\n",
              "      <td>0.169420</td>\n",
              "      <td>0.314820</td>\n",
              "      <td>33.047000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.685151</td>\n",
              "      <td>0.825288</td>\n",
              "      <td>-2.434031</td>\n",
              "      <td>0.450493</td>\n",
              "      <td>3.671155</td>\n",
              "      <td>0.527367</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8 rows × 23 columns</p>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# distribution of target variables (status column) (we are going to predict how many 1 and 0 are there)\n",
        "parkinsons_data['status'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4zTmtcHK6oPf",
        "outputId": "6535a02b-0853-423e-b038-c016c4c6a127"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1    147\n",
              "0     48\n",
              "Name: status, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "1 --> Parkinson's positive\n",
        "\n",
        "0 --> Healthy"
      ],
      "metadata": {
        "id": "yS-eq0Xf7yP_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#grouping the data based on the target variable \n",
        "parkinsons_data.groupby('status').mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "jKk6Zcpp7rzo",
        "outputId": "c1b82073-6b18-4ddd-ffb4-8a5ea409ed8d"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        MDVP:Fo(Hz)  MDVP:Fhi(Hz)  MDVP:Flo(Hz)  MDVP:Jitter(%)  \\\n",
              "status                                                            \n",
              "0        181.937771    223.636750    145.207292        0.003866   \n",
              "1        145.180762    188.441463    106.893558        0.006989   \n",
              "\n",
              "        MDVP:Jitter(Abs)  MDVP:RAP  MDVP:PPQ  Jitter:DDP  MDVP:Shimmer  \\\n",
              "status                                                                   \n",
              "0               0.000023  0.001925  0.002056    0.005776      0.017615   \n",
              "1               0.000051  0.003757  0.003900    0.011273      0.033658   \n",
              "\n",
              "        MDVP:Shimmer(dB)  ...  MDVP:APQ  Shimmer:DDA       NHR        HNR  \\\n",
              "status                    ...                                               \n",
              "0               0.162958  ...  0.013305     0.028511  0.011483  24.678750   \n",
              "1               0.321204  ...  0.027600     0.053027  0.029211  20.974048   \n",
              "\n",
              "            RPDE       DFA   spread1   spread2        D2       PPE  \n",
              "status                                                              \n",
              "0       0.442552  0.695716 -6.759264  0.160292  2.154491  0.123017  \n",
              "1       0.516816  0.725408 -5.333420  0.248133  2.456058  0.233828  \n",
              "\n",
              "[2 rows x 22 columns]"
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              "      <th>MDVP:Fo(Hz)</th>\n",
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              "      <th>spread2</th>\n",
              "      <th>D2</th>\n",
              "      <th>PPE</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>status</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>181.937771</td>\n",
              "      <td>223.636750</td>\n",
              "      <td>145.207292</td>\n",
              "      <td>0.003866</td>\n",
              "      <td>0.000023</td>\n",
              "      <td>0.001925</td>\n",
              "      <td>0.002056</td>\n",
              "      <td>0.005776</td>\n",
              "      <td>0.017615</td>\n",
              "      <td>0.162958</td>\n",
              "      <td>...</td>\n",
              "      <td>0.013305</td>\n",
              "      <td>0.028511</td>\n",
              "      <td>0.011483</td>\n",
              "      <td>24.678750</td>\n",
              "      <td>0.442552</td>\n",
              "      <td>0.695716</td>\n",
              "      <td>-6.759264</td>\n",
              "      <td>0.160292</td>\n",
              "      <td>2.154491</td>\n",
              "      <td>0.123017</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>145.180762</td>\n",
              "      <td>188.441463</td>\n",
              "      <td>106.893558</td>\n",
              "      <td>0.006989</td>\n",
              "      <td>0.000051</td>\n",
              "      <td>0.003757</td>\n",
              "      <td>0.003900</td>\n",
              "      <td>0.011273</td>\n",
              "      <td>0.033658</td>\n",
              "      <td>0.321204</td>\n",
              "      <td>...</td>\n",
              "      <td>0.027600</td>\n",
              "      <td>0.053027</td>\n",
              "      <td>0.029211</td>\n",
              "      <td>20.974048</td>\n",
              "      <td>0.516816</td>\n",
              "      <td>0.725408</td>\n",
              "      <td>-5.333420</td>\n",
              "      <td>0.248133</td>\n",
              "      <td>2.456058</td>\n",
              "      <td>0.233828</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2 rows × 22 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b43c0e18-7b74-4a0c-86a6-476434a01a24')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "        \n",
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              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
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              "          document.querySelector('#df-b43c0e18-7b74-4a0c-86a6-476434a01a24 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
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              "          const element = document.querySelector('#df-b43c0e18-7b74-4a0c-86a6-476434a01a24');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Data Pre-Processing**\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "T_pKQ5jk-EWH"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "seperating the features & Target"
      ],
      "metadata": {
        "id": "OcIE4wMS-SwV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "x = parkinsons_data.drop(columns=['name','status'], axis=1)\n",
        "y = parkinsons_data['status']"
      ],
      "metadata": {
        "id": "8bNaOktN8dfE"
      },
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(x)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iDmB1F0I-9qB",
        "outputId": "d117e78a-db1a-410a-973d-10b6be7e44bd"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "     MDVP:Fo(Hz)  MDVP:Fhi(Hz)  MDVP:Flo(Hz)  MDVP:Jitter(%)  \\\n",
            "0        119.992       157.302        74.997         0.00784   \n",
            "1        122.400       148.650       113.819         0.00968   \n",
            "2        116.682       131.111       111.555         0.01050   \n",
            "3        116.676       137.871       111.366         0.00997   \n",
            "4        116.014       141.781       110.655         0.01284   \n",
            "..           ...           ...           ...             ...   \n",
            "190      174.188       230.978        94.261         0.00459   \n",
            "191      209.516       253.017        89.488         0.00564   \n",
            "192      174.688       240.005        74.287         0.01360   \n",
            "193      198.764       396.961        74.904         0.00740   \n",
            "194      214.289       260.277        77.973         0.00567   \n",
            "\n",
            "     MDVP:Jitter(Abs)  MDVP:RAP  MDVP:PPQ  Jitter:DDP  MDVP:Shimmer  \\\n",
            "0             0.00007   0.00370   0.00554     0.01109       0.04374   \n",
            "1             0.00008   0.00465   0.00696     0.01394       0.06134   \n",
            "2             0.00009   0.00544   0.00781     0.01633       0.05233   \n",
            "3             0.00009   0.00502   0.00698     0.01505       0.05492   \n",
            "4             0.00011   0.00655   0.00908     0.01966       0.06425   \n",
            "..                ...       ...       ...         ...           ...   \n",
            "190           0.00003   0.00263   0.00259     0.00790       0.04087   \n",
            "191           0.00003   0.00331   0.00292     0.00994       0.02751   \n",
            "192           0.00008   0.00624   0.00564     0.01873       0.02308   \n",
            "193           0.00004   0.00370   0.00390     0.01109       0.02296   \n",
            "194           0.00003   0.00295   0.00317     0.00885       0.01884   \n",
            "\n",
            "     MDVP:Shimmer(dB)  ...  MDVP:APQ  Shimmer:DDA      NHR     HNR      RPDE  \\\n",
            "0               0.426  ...   0.02971      0.06545  0.02211  21.033  0.414783   \n",
            "1               0.626  ...   0.04368      0.09403  0.01929  19.085  0.458359   \n",
            "2               0.482  ...   0.03590      0.08270  0.01309  20.651  0.429895   \n",
            "3               0.517  ...   0.03772      0.08771  0.01353  20.644  0.434969   \n",
            "4               0.584  ...   0.04465      0.10470  0.01767  19.649  0.417356   \n",
            "..                ...  ...       ...          ...      ...     ...       ...   \n",
            "190             0.405  ...   0.02745      0.07008  0.02764  19.517  0.448439   \n",
            "191             0.263  ...   0.01879      0.04812  0.01810  19.147  0.431674   \n",
            "192             0.256  ...   0.01667      0.03804  0.10715  17.883  0.407567   \n",
            "193             0.241  ...   0.01588      0.03794  0.07223  19.020  0.451221   \n",
            "194             0.190  ...   0.01373      0.03078  0.04398  21.209  0.462803   \n",
            "\n",
            "          DFA   spread1   spread2        D2       PPE  \n",
            "0    0.815285 -4.813031  0.266482  2.301442  0.284654  \n",
            "1    0.819521 -4.075192  0.335590  2.486855  0.368674  \n",
            "2    0.825288 -4.443179  0.311173  2.342259  0.332634  \n",
            "3    0.819235 -4.117501  0.334147  2.405554  0.368975  \n",
            "4    0.823484 -3.747787  0.234513  2.332180  0.410335  \n",
            "..        ...       ...       ...       ...       ...  \n",
            "190  0.657899 -6.538586  0.121952  2.657476  0.133050  \n",
            "191  0.683244 -6.195325  0.129303  2.784312  0.168895  \n",
            "192  0.655683 -6.787197  0.158453  2.679772  0.131728  \n",
            "193  0.643956 -6.744577  0.207454  2.138608  0.123306  \n",
            "194  0.664357 -5.724056  0.190667  2.555477  0.148569  \n",
            "\n",
            "[195 rows x 22 columns]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "524KGUxc_BGC",
        "outputId": "233ab997-6b99-4eb5-8cb0-08f85a5eb626"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0      1\n",
            "1      1\n",
            "2      1\n",
            "3      1\n",
            "4      1\n",
            "      ..\n",
            "190    0\n",
            "191    0\n",
            "192    0\n",
            "193    0\n",
            "194    0\n",
            "Name: status, Length: 195, dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Splitting the data to training data & Test data"
      ],
      "metadata": {
        "id": "k17vV5S6_d4Y"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2, random_state=2)"
      ],
      "metadata": {
        "id": "v1M7fr8Y_Hjh"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(x.shape, x_train.shape, x_test.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9wecpg-ECRgY",
        "outputId": "93e5129d-aab9-43fa-934d-4a5bd8ec22ac"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(195, 22) (156, 22) (39, 22)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(y.shape, y_train.shape, y_test.shape)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "baGurvrbC24h",
        "outputId": "bc777fc1-c767-4db4-a1de-b7a2948a5661"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(195,) (156,) (39,)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Data Standardization (all the data will be transformed to a same range)"
      ],
      "metadata": {
        "id": "M8HN2CScD0po"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "scaler = StandardScaler()"
      ],
      "metadata": {
        "id": "4bPeLnL7DIw8"
      },
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "scaler.fit(x_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9qy1LWlPEnik",
        "outputId": "5773fd3d-771f-4d00-8557-33554d35e36e"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "StandardScaler()"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x_train = scaler.transform(x_train)\n",
        "\n",
        "x_test = scaler.transform(x_test)"
      ],
      "metadata": {
        "id": "EH3EW-P_FfzJ"
      },
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(x_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MyzF5z58GcbV",
        "outputId": "52754f51-907c-4e22-8f70-ea1e091f49c9"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[ 0.63239631 -0.02731081 -0.87985049 ... -0.97586547 -0.55160318\n",
            "   0.07769494]\n",
            " [-1.05512719 -0.83337041 -0.9284778  ...  0.3981808  -0.61014073\n",
            "   0.39291782]\n",
            " [ 0.02996187 -0.29531068 -1.12211107 ... -0.43937044 -0.62849605\n",
            "  -0.50948408]\n",
            " ...\n",
            " [-0.9096785  -0.6637302  -0.160638   ...  1.22001022 -0.47404629\n",
            "  -0.2159482 ]\n",
            " [-0.35977689  0.19731822 -0.79063679 ... -0.17896029 -0.47272835\n",
            "   0.28181221]\n",
            " [ 1.01957066  0.19922317 -0.61914972 ... -0.716232    1.23632066\n",
            "  -0.05829386]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Model Training**"
      ],
      "metadata": {
        "id": "_75MaS-5RlCW"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Support Vector Machine (SVM) Model"
      ],
      "metadata": {
        "id": "BYKN9uYZRtH_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model = svm.SVC(kernel='linear')"
      ],
      "metadata": {
        "id": "CvWqwQPoGhm7"
      },
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#training the SVM model with training data\n",
        "model.fit(x_train, y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5F7Us8zKfGEt",
        "outputId": "f0281c9e-ad6d-4ec7-ea9e-f62019c7f247"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "SVC(kernel='linear')"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Model evaluation"
      ],
      "metadata": {
        "id": "apOLyd8ygZJc"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Accuracy Score"
      ],
      "metadata": {
        "id": "GY27jdCGgdF0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# accuracy score on training data\n",
        "x_train_prediction = model.predict(x_train)\n",
        "training_data_accuracy = accuracy_score(y_train, x_train_prediction)"
      ],
      "metadata": {
        "id": "Vyz8zAX8fciK"
      },
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print('accuracy score of training data :', training_data_accuracy)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_Pksgn1CheVW",
        "outputId": "dfb157c0-b2f9-430f-a03b-4ec9162f1dc8"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "accuracy score of training data : 0.8846153846153846\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Here, We are getting the accuracy score for training data as 0.88, which is around 88% out of 100. \n",
        "\n",
        "if the accuracy score is more than 75%, your model is working fine\n",
        "\n",
        "example: for 100 cases, your model can predict correctly for 88 cases"
      ],
      "metadata": {
        "id": "dIMA4E7viQ98"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# accuracy score on testing data\n",
        "x_test_prediction = model.predict(x_test)\n",
        "test_data_accuracy = accuracy_score(y_test, x_test_prediction)"
      ],
      "metadata": {
        "id": "Tas6UaRmiEUx"
      },
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print('accuracy score of testing data :', test_data_accuracy)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PJFYK0x_jPco",
        "outputId": "5657bad3-1a8d-42ba-e0a2-f472b2dbad23"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "accuracy score of testing data : 0.8717948717948718\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "we have found the accuracy score of training data as well.\n",
        "\n",
        "because, our training data accuracy and the test data accuracy should have the same value. with minimum differences.\n",
        "\n",
        "else\n",
        "\n",
        "our model is overtrained or it is overfitted or underfitted."
      ],
      "metadata": {
        "id": "NDcNDbiAn0Lk"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Building a Predictive system**"
      ],
      "metadata": {
        "id": "APe9lbwfoXFk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "input_data = (177.87600,192.92100,168.01300,0.00411,0.00002,0.00233,0.00241,0.00700,0.02126,0.18900,0.01154,0.01347,0.01612,0.03463,0.00586,23.21600,0.360148,0.778834,-6.149653,0.218037,2.477082,0.165827)\n",
        "\n",
        "# changing input data to a numpy array\n",
        "input_data_as_numpy_array = np.asarray(input_data)\n",
        "\n",
        "# reshape the numpy array\n",
        "input_data_reshaped = input_data_as_numpy_array.reshape(1,-1)\n",
        "\n",
        "# standardize the data \n",
        "std_data = scaler.transform(input_data_reshaped)\n",
        "\n",
        "prediction = model.predict(std_data)\n",
        "print(prediction)\n",
        "\n",
        "if (prediction[0] == 0):\n",
        "  print('The Person does not have Parkinson disease')\n",
        "\n",
        "else:\n",
        "  print('The Person has Parkinson')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "w2-6Qxq9tCa4",
        "outputId": "cf6a3c69-2890-48ce-dd6b-07b8cfb61582"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[1]\n",
            "The Person has Parkinson\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/sklearn/base.py:451: UserWarning: X does not have valid feature names, but StandardScaler was fitted with feature names\n",
            "  \"X does not have valid feature names, but\"\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "tOfHQP-FJ81V"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}