Regression_floods_kaggle_compet_first_Model.ipynb

{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.13","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":73278,"databundleVersionId":8121328,"sourceType":"competition"}],"dockerImageVersionId":30698,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2024-05-21T13:34:41.778752Z","iopub.execute_input":"2024-05-21T13:34:41.779776Z","iopub.status.idle":"2024-05-21T13:34:42.245699Z","shell.execute_reply.started":"2024-05-21T13:34:41.779705Z","shell.execute_reply":"2024-05-21T13:34:42.244572Z"},"trusted":true},"execution_count":1,"outputs":[{"name":"stdout","text":"/kaggle/input/playground-series-s4e5/sample_submission.csv\n/kaggle/input/playground-series-s4e5/train.csv\n/kaggle/input/playground-series-s4e5/test.csv\n","output_type":"stream"}]},{"cell_type":"markdown","source":"# Libraries","metadata":{}},{"cell_type":"code","source":"import xgboost as xgb\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import r2_score","metadata":{"execution":{"iopub.status.busy":"2024-05-21T13:34:42.248051Z","iopub.execute_input":"2024-05-21T13:34:42.248760Z","iopub.status.idle":"2024-05-21T13:34:42.802827Z","shell.execute_reply.started":"2024-05-21T13:34:42.248691Z","shell.execute_reply":"2024-05-21T13:34:42.801686Z"},"trusted":true},"execution_count":2,"outputs":[]},{"cell_type":"markdown","source":"# folders","metadata":{}},{"cell_type":"code","source":"path_train = r'/kaggle/input/playground-series-s4e5/train.csv'\npath_test = r'/kaggle/input/playground-series-s4e5/test.csv'\npath_submission = r'/kaggle/input/playground-series-s4e5/sample_submission.csv'","metadata":{"execution":{"iopub.status.busy":"2024-05-21T13:34:42.804323Z","iopub.execute_input":"2024-05-21T13:34:42.804662Z","iopub.status.idle":"2024-05-21T13:34:42.811346Z","shell.execute_reply.started":"2024-05-21T13:34:42.804634Z","shell.execute_reply":"2024-05-21T13:34:42.809711Z"},"trusted":true},"execution_count":3,"outputs":[]},{"cell_type":"markdown","source":"# read data","metadata":{}},{"cell_type":"code","source":"orig_train = pd.read_csv(path_train,index_col=['id'])\norig_train.head()","metadata":{"execution":{"iopub.status.busy":"2024-05-21T13:34:42.814554Z","iopub.execute_input":"2024-05-21T13:34:42.815488Z","iopub.status.idle":"2024-05-21T13:34:44.783517Z","shell.execute_reply.started":"2024-05-21T13:34:42.815449Z","shell.execute_reply":"2024-05-21T13:34:44.782313Z"},"trusted":true},"execution_count":4,"outputs":[{"execution_count":4,"output_type":"execute_result","data":{"text/plain":"    MonsoonIntensity  TopographyDrainage  RiverManagement  Deforestation  \\\nid                                                                         \n0                  5                   8                5              8   \n1                  6                   7                4              4   \n2                  6                   5                6              7   \n3                  3                   4                6              5   \n4                  5                   3                2              6   \n\n    Urbanization  ClimateChange  DamsQuality  Siltation  \\\nid                                                        \n0              6              4            4          3   \n1              8              8            3          5   \n2              3              7            1          5   \n3              4              8            4          7   \n4              4              4            3          3   \n\n    AgriculturalPractices  Encroachments  ...  DrainageSystems  \\\nid                                        ...                    \n0                       3              4  ...                5   \n1                       4              6  ...                7   \n2                       4              5  ...                7   \n3                       6              8  ...                2   \n4                       3              3  ...                2   \n\n    CoastalVulnerability  Landslides  Watersheds  DeterioratingInfrastructure  \\\nid                                                                              \n0                      3           3           5                            4   \n1                      2           0           3                            5   \n2                      3           7           5                            6   \n3                      4           7           4                            4   \n4                      2           6           6                            4   \n\n    PopulationScore  WetlandLoss  InadequatePlanning  PoliticalFactors  \\\nid                                                                       \n0                 7            5                   7                 3   \n1                 3            3                   4                 3   \n2                 8            2                   3                 3   \n3                 6            5                   7                 5   \n4                 1            2                   3                 5   \n\n    FloodProbability  \nid                    \n0              0.445  \n1              0.450  \n2              0.530  \n3              0.535  \n4              0.415  \n\n[5 rows x 21 columns]","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>MonsoonIntensity</th>\n      <th>TopographyDrainage</th>\n      <th>RiverManagement</th>\n      <th>Deforestation</th>\n      <th>Urbanization</th>\n      <th>ClimateChange</th>\n      <th>DamsQuality</th>\n      <th>Siltation</th>\n      <th>AgriculturalPractices</th>\n      <th>Encroachments</th>\n      <th>...</th>\n      <th>DrainageSystems</th>\n      <th>CoastalVulnerability</th>\n      <th>Landslides</th>\n      <th>Watersheds</th>\n      <th>DeterioratingInfrastructure</th>\n      <th>PopulationScore</th>\n      <th>WetlandLoss</th>\n      <th>InadequatePlanning</th>\n      <th>PoliticalFactors</th>\n      <th>FloodProbability</th>\n    </tr>\n    <tr>\n      <th>id</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>5</td>\n      <td>8</td>\n      <td>5</td>\n      <td>8</td>\n      <td>6</td>\n      <td>4</td>\n      <td>4</td>\n      <td>3</td>\n      <td>3</td>\n      <td>4</td>\n      <td>...</td>\n      <td>5</td>\n      <td>3</td>\n      <td>3</td>\n      <td>5</td>\n      <td>4</td>\n      <td>7</td>\n      <td>5</td>\n      <td>7</td>\n      <td>3</td>\n      <td>0.445</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>6</td>\n      <td>7</td>\n      <td>4</td>\n      <td>4</td>\n      <td>8</td>\n      <td>8</td>\n      <td>3</td>\n      <td>5</td>\n      <td>4</td>\n      <td>6</td>\n      <td>...</td>\n      <td>7</td>\n      <td>2</td>\n      <td>0</td>\n      <td>3</td>\n      <td>5</td>\n      <td>3</td>\n      <td>3</td>\n      <td>4</td>\n      <td>3</td>\n      <td>0.450</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>6</td>\n      <td>5</td>\n      <td>6</td>\n      <td>7</td>\n      <td>3</td>\n      <td>7</td>\n      <td>1</td>\n      <td>5</td>\n      <td>4</td>\n      <td>5</td>\n      <td>...</td>\n      <td>7</td>\n      <td>3</td>\n      <td>7</td>\n      <td>5</td>\n      <td>6</td>\n      <td>8</td>\n      <td>2</td>\n      <td>3</td>\n      <td>3</td>\n      <td>0.530</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>3</td>\n      <td>4</td>\n      <td>6</td>\n      <td>5</td>\n      <td>4</td>\n      <td>8</td>\n      <td>4</td>\n      <td>7</td>\n      <td>6</td>\n      <td>8</td>\n      <td>...</td>\n      <td>2</td>\n      <td>4</td>\n      <td>7</td>\n      <td>4</td>\n      <td>4</td>\n      <td>6</td>\n      <td>5</td>\n      <td>7</td>\n      <td>5</td>\n      <td>0.535</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>5</td>\n      <td>3</td>\n      <td>2</td>\n      <td>6</td>\n      <td>4</td>\n      <td>4</td>\n      <td>3</td>\n      <td>3</td>\n      <td>3</td>\n      <td>3</td>\n      <td>...</td>\n      <td>2</td>\n      <td>2</td>\n      <td>6</td>\n      <td>6</td>\n      <td>4</td>\n      <td>1</td>\n      <td>2</td>\n      <td>3</td>\n      <td>5</td>\n      <td>0.415</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 21 columns</p>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"orig_test = pd.read_csv(path_test, index_col=['id'])\norig_test.head()","metadata":{"execution":{"iopub.status.busy":"2024-05-21T13:34:44.784693Z","iopub.execute_input":"2024-05-21T13:34:44.785036Z","iopub.status.idle":"2024-05-21T13:34:45.937719Z","shell.execute_reply.started":"2024-05-21T13:34:44.785008Z","shell.execute_reply":"2024-05-21T13:34:45.936605Z"},"trusted":true},"execution_count":5,"outputs":[{"execution_count":5,"output_type":"execute_result","data":{"text/plain":"         MonsoonIntensity  TopographyDrainage  RiverManagement  Deforestation  \\\nid                                                                              \n1117957                 4                   6                3              5   \n1117958                 4                   4                2              9   \n1117959                 1                   3                6              5   \n1117960                 2                   4                4              6   \n1117961                 6                   3                2              4   \n\n         Urbanization  ClimateChange  DamsQuality  Siltation  \\\nid                                                             \n1117957             6              7            8          7   \n1117958             5              5            4          7   \n1117959             7              2            4          6   \n1117960             4              5            4          3   \n1117961             6              4            5          5   \n\n         AgriculturalPractices  Encroachments  \\\nid                                              \n1117957                      8              4   \n1117958                      5              4   \n1117959                      4              2   \n1117960                      4              4   \n1117961                      3              7   \n\n         IneffectiveDisasterPreparedness  DrainageSystems  \\\nid                                                          \n1117957                                8                5   \n1117958                                2                4   \n1117959                                7                9   \n1117960                                7                8   \n1117961                                4                3   \n\n         CoastalVulnerability  Landslides  Watersheds  \\\nid                                                      \n1117957                     7           5           6   \n1117958                     7           4           5   \n1117959                     2           5           5   \n1117960                     4           6           7   \n1117961                     2           6           4   \n\n         DeterioratingInfrastructure  PopulationScore  WetlandLoss  \\\nid                                                                   \n1117957                            3                6            4   \n1117958                            1                7            4   \n1117959                            2                3            6   \n1117960                            6                4            2   \n1117961                            6                8            4   \n\n         InadequatePlanning  PoliticalFactors  \nid                                             \n1117957                   4                 5  \n1117958                   4                 3  \n1117959                   8                 3  \n1117960                   4                 4  \n1117961                   5                 5  ","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>MonsoonIntensity</th>\n      <th>TopographyDrainage</th>\n      <th>RiverManagement</th>\n      <th>Deforestation</th>\n      <th>Urbanization</th>\n      <th>ClimateChange</th>\n      <th>DamsQuality</th>\n      <th>Siltation</th>\n      <th>AgriculturalPractices</th>\n      <th>Encroachments</th>\n      <th>IneffectiveDisasterPreparedness</th>\n      <th>DrainageSystems</th>\n      <th>CoastalVulnerability</th>\n      <th>Landslides</th>\n      <th>Watersheds</th>\n      <th>DeterioratingInfrastructure</th>\n      <th>PopulationScore</th>\n      <th>WetlandLoss</th>\n      <th>InadequatePlanning</th>\n      <th>PoliticalFactors</th>\n    </tr>\n    <tr>\n      <th>id</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>1117957</th>\n      <td>4</td>\n      <td>6</td>\n      <td>3</td>\n      <td>5</td>\n      <td>6</td>\n      <td>7</td>\n      <td>8</td>\n      <td>7</td>\n      <td>8</td>\n      <td>4</td>\n      <td>8</td>\n      <td>5</td>\n      <td>7</td>\n      <td>5</td>\n      <td>6</td>\n      <td>3</td>\n      <td>6</td>\n      <td>4</td>\n      <td>4</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>1117958</th>\n      <td>4</td>\n      <td>4</td>\n      <td>2</td>\n      <td>9</td>\n      <td>5</td>\n      <td>5</td>\n      <td>4</td>\n      <td>7</td>\n      <td>5</td>\n      <td>4</td>\n      <td>2</td>\n      <td>4</td>\n      <td>7</td>\n      <td>4</td>\n      <td>5</td>\n      <td>1</td>\n      <td>7</td>\n      <td>4</td>\n      <td>4</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>1117959</th>\n      <td>1</td>\n      <td>3</td>\n      <td>6</td>\n      <td>5</td>\n      <td>7</td>\n      <td>2</td>\n      <td>4</td>\n      <td>6</td>\n      <td>4</td>\n      <td>2</td>\n      <td>7</td>\n      <td>9</td>\n      <td>2</td>\n      <td>5</td>\n      <td>5</td>\n      <td>2</td>\n      <td>3</td>\n      <td>6</td>\n      <td>8</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>1117960</th>\n      <td>2</td>\n      <td>4</td>\n      <td>4</td>\n      <td>6</td>\n      <td>4</td>\n      <td>5</td>\n      <td>4</td>\n      <td>3</td>\n      <td>4</td>\n      <td>4</td>\n      <td>7</td>\n      <td>8</td>\n      <td>4</td>\n      <td>6</td>\n      <td>7</td>\n      <td>6</td>\n      <td>4</td>\n      <td>2</td>\n      <td>4</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>1117961</th>\n      <td>6</td>\n      <td>3</td>\n      <td>2</td>\n      <td>4</td>\n      <td>6</td>\n      <td>4</td>\n      <td>5</td>\n      <td>5</td>\n      <td>3</td>\n      <td>7</td>\n      <td>4</td>\n      <td>3</td>\n      <td>2</td>\n      <td>6</td>\n      <td>4</td>\n      <td>6</td>\n      <td>8</td>\n      <td>4</td>\n      <td>5</td>\n      <td>5</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"orig_train.isna().sum()","metadata":{"execution":{"iopub.status.busy":"2024-05-21T13:34:45.939105Z","iopub.execute_input":"2024-05-21T13:34:45.939453Z","iopub.status.idle":"2024-05-21T13:34:45.970950Z","shell.execute_reply.started":"2024-05-21T13:34:45.939424Z","shell.execute_reply":"2024-05-21T13:34:45.969550Z"},"trusted":true},"execution_count":6,"outputs":[{"execution_count":6,"output_type":"execute_result","data":{"text/plain":"MonsoonIntensity                   0\nTopographyDrainage                 0\nRiverManagement                    0\nDeforestation                      0\nUrbanization                       0\nClimateChange                      0\nDamsQuality                        0\nSiltation                          0\nAgriculturalPractices              0\nEncroachments                      0\nIneffectiveDisasterPreparedness    0\nDrainageSystems                    0\nCoastalVulnerability               0\nLandslides                         0\nWatersheds                         0\nDeterioratingInfrastructure        0\nPopulationScore                    0\nWetlandLoss                        0\nInadequatePlanning                 0\nPoliticalFactors                   0\nFloodProbability                   0\ndtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"orig_train.describe()","metadata":{"execution":{"iopub.status.busy":"2024-05-21T13:34:45.972240Z","iopub.execute_input":"2024-05-21T13:34:45.972587Z","iopub.status.idle":"2024-05-21T13:34:46.791909Z","shell.execute_reply.started":"2024-05-21T13:34:45.972557Z","shell.execute_reply":"2024-05-21T13:34:46.790693Z"},"trusted":true},"execution_count":7,"outputs":[{"execution_count":7,"output_type":"execute_result","data":{"text/plain":"       MonsoonIntensity  TopographyDrainage  RiverManagement  Deforestation  \\\ncount      1.117957e+06        1.117957e+06     1.117957e+06   1.117957e+06   \nmean       4.921450e+00        4.926671e+00     4.955322e+00   4.942240e+00   \nstd        2.056387e+00        2.093879e+00     2.072186e+00   2.051689e+00   \nmin        0.000000e+00        0.000000e+00     0.000000e+00   0.000000e+00   \n25%        3.000000e+00        3.000000e+00     4.000000e+00   4.000000e+00   \n50%        5.000000e+00        5.000000e+00     5.000000e+00   5.000000e+00   \n75%        6.000000e+00        6.000000e+00     6.000000e+00   6.000000e+00   \nmax        1.600000e+01        1.800000e+01     1.600000e+01   1.700000e+01   \n\n       Urbanization  ClimateChange   DamsQuality     Siltation  \\\ncount  1.117957e+06   1.117957e+06  1.117957e+06  1.117957e+06   \nmean   4.942517e+00   4.934093e+00  4.955878e+00  4.927791e+00   \nstd    2.083391e+00   2.057742e+00  2.083063e+00  2.065992e+00   \nmin    0.000000e+00   0.000000e+00  0.000000e+00  0.000000e+00   \n25%    3.000000e+00   3.000000e+00  4.000000e+00  3.000000e+00   \n50%    5.000000e+00   5.000000e+00  5.000000e+00  5.000000e+00   \n75%    6.000000e+00   6.000000e+00  6.000000e+00  6.000000e+00   \nmax    1.700000e+01   1.700000e+01  1.600000e+01  1.600000e+01   \n\n       AgriculturalPractices  Encroachments  ...  DrainageSystems  \\\ncount           1.117957e+06   1.117957e+06  ...     1.117957e+06   \nmean            4.942619e+00   4.949230e+00  ...     4.946893e+00   \nstd             2.068545e+00   2.083324e+00  ...     2.072333e+00   \nmin             0.000000e+00   0.000000e+00  ...     0.000000e+00   \n25%             3.000000e+00   4.000000e+00  ...     4.000000e+00   \n50%             5.000000e+00   5.000000e+00  ...     5.000000e+00   \n75%             6.000000e+00   6.000000e+00  ...     6.000000e+00   \nmax             1.600000e+01   1.800000e+01  ...     1.700000e+01   \n\n       CoastalVulnerability    Landslides    Watersheds  \\\ncount          1.117957e+06  1.117957e+06  1.117957e+06   \nmean           4.953999e+00  4.931376e+00  4.929032e+00   \nstd            2.088899e+00  2.078287e+00  2.082395e+00   \nmin            0.000000e+00  0.000000e+00  0.000000e+00   \n25%            3.000000e+00  3.000000e+00  3.000000e+00   \n50%            5.000000e+00  5.000000e+00  5.000000e+00   \n75%            6.000000e+00  6.000000e+00  6.000000e+00   \nmax            1.700000e+01  1.600000e+01  1.600000e+01   \n\n       DeterioratingInfrastructure  PopulationScore   WetlandLoss  \\\ncount                 1.117957e+06     1.117957e+06  1.117957e+06   \nmean                  4.925907e+00     4.927520e+00  4.950859e+00   \nstd                   2.064813e+00     2.074176e+00  2.068696e+00   \nmin                   0.000000e+00     0.000000e+00  0.000000e+00   \n25%                   3.000000e+00     3.000000e+00  4.000000e+00   \n50%                   5.000000e+00     5.000000e+00  5.000000e+00   \n75%                   6.000000e+00     6.000000e+00  6.000000e+00   \nmax                   1.700000e+01     1.800000e+01  1.900000e+01   \n\n       InadequatePlanning  PoliticalFactors  FloodProbability  \ncount        1.117957e+06      1.117957e+06      1.117957e+06  \nmean         4.940587e+00      4.939004e+00      5.044803e-01  \nstd          2.081123e+00      2.090350e+00      5.102610e-02  \nmin          0.000000e+00      0.000000e+00      2.850000e-01  \n25%          3.000000e+00      3.000000e+00      4.700000e-01  \n50%          5.000000e+00      5.000000e+00      5.050000e-01  \n75%          6.000000e+00      6.000000e+00      5.400000e-01  \nmax          1.600000e+01      1.600000e+01      7.250000e-01  \n\n[8 rows x 21 columns]","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>MonsoonIntensity</th>\n      <th>TopographyDrainage</th>\n      <th>RiverManagement</th>\n      <th>Deforestation</th>\n      <th>Urbanization</th>\n      <th>ClimateChange</th>\n      <th>DamsQuality</th>\n      <th>Siltation</th>\n      <th>AgriculturalPractices</th>\n      <th>Encroachments</th>\n      <th>...</th>\n      <th>DrainageSystems</th>\n      <th>CoastalVulnerability</th>\n      <th>Landslides</th>\n      <th>Watersheds</th>\n      <th>DeterioratingInfrastructure</th>\n      <th>PopulationScore</th>\n      <th>WetlandLoss</th>\n      <th>InadequatePlanning</th>\n      <th>PoliticalFactors</th>\n      <th>FloodProbability</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>1.117957e+06</td>\n      <td>1.117957e+06</td>\n      <td>1.117957e+06</td>\n      <td>1.117957e+06</td>\n      <td>1.117957e+06</td>\n      <td>1.117957e+06</td>\n      <td>1.117957e+06</td>\n      <td>1.117957e+06</td>\n      <td>1.117957e+06</td>\n      <td>1.117957e+06</td>\n      <td>...</td>\n      <td>1.117957e+06</td>\n      <td>1.117957e+06</td>\n      <td>1.117957e+06</td>\n      <td>1.117957e+06</td>\n      <td>1.117957e+06</td>\n      <td>1.117957e+06</td>\n      <td>1.117957e+06</td>\n      <td>1.117957e+06</td>\n      <td>1.117957e+06</td>\n      <td>1.117957e+06</td>\n    </tr>\n    <tr>\n      <th>mean</th>\n      <td>4.921450e+00</td>\n      <td>4.926671e+00</td>\n      <td>4.955322e+00</td>\n      <td>4.942240e+00</td>\n      <td>4.942517e+00</td>\n      <td>4.934093e+00</td>\n      <td>4.955878e+00</td>\n      <td>4.927791e+00</td>\n      <td>4.942619e+00</td>\n      <td>4.949230e+00</td>\n      <td>...</td>\n      <td>4.946893e+00</td>\n      <td>4.953999e+00</td>\n      <td>4.931376e+00</td>\n      <td>4.929032e+00</td>\n      <td>4.925907e+00</td>\n      <td>4.927520e+00</td>\n      <td>4.950859e+00</td>\n      <td>4.940587e+00</td>\n      <td>4.939004e+00</td>\n      <td>5.044803e-01</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>2.056387e+00</td>\n      <td>2.093879e+00</td>\n      <td>2.072186e+00</td>\n      <td>2.051689e+00</td>\n      <td>2.083391e+00</td>\n      <td>2.057742e+00</td>\n      <td>2.083063e+00</td>\n      <td>2.065992e+00</td>\n      <td>2.068545e+00</td>\n      <td>2.083324e+00</td>\n      <td>...</td>\n      <td>2.072333e+00</td>\n      <td>2.088899e+00</td>\n      <td>2.078287e+00</td>\n      <td>2.082395e+00</td>\n      <td>2.064813e+00</td>\n      <td>2.074176e+00</td>\n      <td>2.068696e+00</td>\n      <td>2.081123e+00</td>\n      <td>2.090350e+00</td>\n      <td>5.102610e-02</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>0.000000e+00</td>\n      <td>0.000000e+00</td>\n      <td>0.000000e+00</td>\n      <td>0.000000e+00</td>\n      <td>0.000000e+00</td>\n      <td>0.000000e+00</td>\n      <td>0.000000e+00</td>\n      <td>0.000000e+00</td>\n      <td>0.000000e+00</td>\n      <td>0.000000e+00</td>\n      <td>...</td>\n      <td>0.000000e+00</td>\n      <td>0.000000e+00</td>\n      <td>0.000000e+00</td>\n      <td>0.000000e+00</td>\n      <td>0.000000e+00</td>\n      <td>0.000000e+00</td>\n      <td>0.000000e+00</td>\n      <td>0.000000e+00</td>\n      <td>0.000000e+00</td>\n      <td>2.850000e-01</td>\n    </tr>\n    <tr>\n      <th>25%</th>\n      <td>3.000000e+00</td>\n      <td>3.000000e+00</td>\n      <td>4.000000e+00</td>\n      <td>4.000000e+00</td>\n      <td>3.000000e+00</td>\n      <td>3.000000e+00</td>\n      <td>4.000000e+00</td>\n      <td>3.000000e+00</td>\n      <td>3.000000e+00</td>\n      <td>4.000000e+00</td>\n      <td>...</td>\n      <td>4.000000e+00</td>\n      <td>3.000000e+00</td>\n      <td>3.000000e+00</td>\n      <td>3.000000e+00</td>\n      <td>3.000000e+00</td>\n      <td>3.000000e+00</td>\n      <td>4.000000e+00</td>\n      <td>3.000000e+00</td>\n      <td>3.000000e+00</td>\n      <td>4.700000e-01</td>\n    </tr>\n    <tr>\n      <th>50%</th>\n      <td>5.000000e+00</td>\n      <td>5.000000e+00</td>\n      <td>5.000000e+00</td>\n      <td>5.000000e+00</td>\n      <td>5.000000e+00</td>\n      <td>5.000000e+00</td>\n      <td>5.000000e+00</td>\n      <td>5.000000e+00</td>\n      <td>5.000000e+00</td>\n      <td>5.000000e+00</td>\n      <td>...</td>\n      <td>5.000000e+00</td>\n      <td>5.000000e+00</td>\n      <td>5.000000e+00</td>\n      <td>5.000000e+00</td>\n      <td>5.000000e+00</td>\n      <td>5.000000e+00</td>\n      <td>5.000000e+00</td>\n      <td>5.000000e+00</td>\n      <td>5.000000e+00</td>\n      <td>5.050000e-01</td>\n    </tr>\n    <tr>\n      <th>75%</th>\n      <td>6.000000e+00</td>\n      <td>6.000000e+00</td>\n      <td>6.000000e+00</td>\n      <td>6.000000e+00</td>\n      <td>6.000000e+00</td>\n      <td>6.000000e+00</td>\n      <td>6.000000e+00</td>\n      <td>6.000000e+00</td>\n      <td>6.000000e+00</td>\n      <td>6.000000e+00</td>\n      <td>...</td>\n      <td>6.000000e+00</td>\n      <td>6.000000e+00</td>\n      <td>6.000000e+00</td>\n      <td>6.000000e+00</td>\n      <td>6.000000e+00</td>\n      <td>6.000000e+00</td>\n      <td>6.000000e+00</td>\n      <td>6.000000e+00</td>\n      <td>6.000000e+00</td>\n      <td>5.400000e-01</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>1.600000e+01</td>\n      <td>1.800000e+01</td>\n      <td>1.600000e+01</td>\n      <td>1.700000e+01</td>\n      <td>1.700000e+01</td>\n      <td>1.700000e+01</td>\n      <td>1.600000e+01</td>\n      <td>1.600000e+01</td>\n      <td>1.600000e+01</td>\n      <td>1.800000e+01</td>\n      <td>...</td>\n      <td>1.700000e+01</td>\n      <td>1.700000e+01</td>\n      <td>1.600000e+01</td>\n      <td>1.600000e+01</td>\n      <td>1.700000e+01</td>\n      <td>1.800000e+01</td>\n      <td>1.900000e+01</td>\n      <td>1.600000e+01</td>\n      <td>1.600000e+01</td>\n      <td>7.250000e-01</td>\n    </tr>\n  </tbody>\n</table>\n<p>8 rows × 21 columns</p>\n</div>"},"metadata":{}}]},{"cell_type":"markdown","source":"# train data split","metadata":{}},{"cell_type":"code","source":"X = orig_train.drop(['FloodProbability'],axis=1)\nY = orig_train[['FloodProbability']]\ntrain_x, valid_x, train_y, valid_y = train_test_split(X,Y, test_size=0.2)\nvalid_x.head()","metadata":{"execution":{"iopub.status.busy":"2024-05-21T13:34:46.793411Z","iopub.execute_input":"2024-05-21T13:34:46.794274Z","iopub.status.idle":"2024-05-21T13:34:47.176848Z","shell.execute_reply.started":"2024-05-21T13:34:46.794235Z","shell.execute_reply":"2024-05-21T13:34:47.175723Z"},"trusted":true},"execution_count":8,"outputs":[{"execution_count":8,"output_type":"execute_result","data":{"text/plain":"         MonsoonIntensity  TopographyDrainage  RiverManagement  Deforestation  \\\nid                                                                              \n555870                  4                   5                4             11   \n618052                  2                   2                4              6   \n526732                  6                   7                6              6   \n574044                  8                   5               10              2   \n1043773                 2                   3                1              9   \n\n         Urbanization  ClimateChange  DamsQuality  Siltation  \\\nid                                                             \n555870              4              5            1          2   \n618052              7              6            2          6   \n526732              4              3            2         10   \n574044              5              2            5          6   \n1043773             2              5            6          8   \n\n         AgriculturalPractices  Encroachments  \\\nid                                              \n555870                       4              5   \n618052                      10              4   \n526732                       4              1   \n574044                       6              3   \n1043773                      4              5   \n\n         IneffectiveDisasterPreparedness  DrainageSystems  \\\nid                                                          \n555870                                 7                6   \n618052                                 3                1   \n526732                                 8                4   \n574044                                 9                5   \n1043773                                4                4   \n\n         CoastalVulnerability  Landslides  Watersheds  \\\nid                                                      \n555870                      6           6           6   \n618052                      8           5           4   \n526732                      3           5           5   \n574044                      3           8           5   \n1043773                     8           5           3   \n\n         DeterioratingInfrastructure  PopulationScore  WetlandLoss  \\\nid                                                                   \n555870                             5                8            5   \n618052                             5                4            4   \n526732                             2                2            2   \n574044                             3                4            3   \n1043773                            3                4            4   \n\n         InadequatePlanning  PoliticalFactors  \nid                                             \n555870                    5                 6  \n618052                    8                 6  \n526732                    5                 8  \n574044                    3                 2  \n1043773                   6                 6  ","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>MonsoonIntensity</th>\n      <th>TopographyDrainage</th>\n      <th>RiverManagement</th>\n      <th>Deforestation</th>\n      <th>Urbanization</th>\n      <th>ClimateChange</th>\n      <th>DamsQuality</th>\n      <th>Siltation</th>\n      <th>AgriculturalPractices</th>\n      <th>Encroachments</th>\n      <th>IneffectiveDisasterPreparedness</th>\n      <th>DrainageSystems</th>\n      <th>CoastalVulnerability</th>\n      <th>Landslides</th>\n      <th>Watersheds</th>\n      <th>DeterioratingInfrastructure</th>\n      <th>PopulationScore</th>\n      <th>WetlandLoss</th>\n      <th>InadequatePlanning</th>\n      <th>PoliticalFactors</th>\n    </tr>\n    <tr>\n      <th>id</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>555870</th>\n      <td>4</td>\n      <td>5</td>\n      <td>4</td>\n      <td>11</td>\n      <td>4</td>\n      <td>5</td>\n      <td>1</td>\n      <td>2</td>\n      <td>4</td>\n      <td>5</td>\n      <td>7</td>\n      <td>6</td>\n      <td>6</td>\n      <td>6</td>\n      <td>6</td>\n      <td>5</td>\n      <td>8</td>\n      <td>5</td>\n      <td>5</td>\n      <td>6</td>\n    </tr>\n    <tr>\n      <th>618052</th>\n      <td>2</td>\n      <td>2</td>\n      <td>4</td>\n      <td>6</td>\n      <td>7</td>\n      <td>6</td>\n      <td>2</td>\n      <td>6</td>\n      <td>10</td>\n      <td>4</td>\n      <td>3</td>\n      <td>1</td>\n      <td>8</td>\n      <td>5</td>\n      <td>4</td>\n      <td>5</td>\n      <td>4</td>\n      <td>4</td>\n      <td>8</td>\n      <td>6</td>\n    </tr>\n    <tr>\n      <th>526732</th>\n      <td>6</td>\n      <td>7</td>\n      <td>6</td>\n      <td>6</td>\n      <td>4</td>\n      <td>3</td>\n      <td>2</td>\n      <td>10</td>\n      <td>4</td>\n      <td>1</td>\n      <td>8</td>\n      <td>4</td>\n      <td>3</td>\n      <td>5</td>\n      <td>5</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>5</td>\n      <td>8</td>\n    </tr>\n    <tr>\n      <th>574044</th>\n      <td>8</td>\n      <td>5</td>\n      <td>10</td>\n      <td>2</td>\n      <td>5</td>\n      <td>2</td>\n      <td>5</td>\n      <td>6</td>\n      <td>6</td>\n      <td>3</td>\n      <td>9</td>\n      <td>5</td>\n      <td>3</td>\n      <td>8</td>\n      <td>5</td>\n      <td>3</td>\n      <td>4</td>\n      <td>3</td>\n      <td>3</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>1043773</th>\n      <td>2</td>\n      <td>3</td>\n      <td>1</td>\n      <td>9</td>\n      <td>2</td>\n      <td>5</td>\n      <td>6</td>\n      <td>8</td>\n      <td>4</td>\n      <td>5</td>\n      <td>4</td>\n      <td>4</td>\n      <td>8</td>\n      <td>5</td>\n      <td>3</td>\n      <td>3</td>\n      <td>4</td>\n      <td>4</td>\n      <td>6</td>\n      <td>6</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"train_y.head()","metadata":{"execution":{"iopub.status.busy":"2024-05-21T13:34:47.178073Z","iopub.execute_input":"2024-05-21T13:34:47.178386Z","iopub.status.idle":"2024-05-21T13:34:47.189310Z","shell.execute_reply.started":"2024-05-21T13:34:47.178360Z","shell.execute_reply":"2024-05-21T13:34:47.187893Z"},"trusted":true},"execution_count":9,"outputs":[{"execution_count":9,"output_type":"execute_result","data":{"text/plain":"        FloodProbability\nid                      \n534821             0.625\n925676             0.455\n973432             0.510\n668026             0.520\n203030             0.625","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>FloodProbability</th>\n    </tr>\n    <tr>\n      <th>id</th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>534821</th>\n      <td>0.625</td>\n    </tr>\n    <tr>\n      <th>925676</th>\n      <td>0.455</td>\n    </tr>\n    <tr>\n      <th>973432</th>\n      <td>0.510</td>\n    </tr>\n    <tr>\n      <th>668026</th>\n      <td>0.520</td>\n    </tr>\n    <tr>\n      <th>203030</th>\n      <td>0.625</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"markdown","source":"# xgb model","metadata":{}},{"cell_type":"code","source":"model = xgb.XGBRegressor(n_jobs=-1)\nmodel.fit(train_x, train_y)","metadata":{"execution":{"iopub.status.busy":"2024-05-21T13:34:47.193517Z","iopub.execute_input":"2024-05-21T13:34:47.193900Z","iopub.status.idle":"2024-05-21T13:34:53.926299Z","shell.execute_reply.started":"2024-05-21T13:34:47.193870Z","shell.execute_reply":"2024-05-21T13:34:53.925044Z"},"trusted":true},"execution_count":10,"outputs":[{"execution_count":10,"output_type":"execute_result","data":{"text/plain":"XGBRegressor(base_score=None, booster=None, callbacks=None,\n             colsample_bylevel=None, colsample_bynode=None,\n             colsample_bytree=None, device=None, early_stopping_rounds=None,\n             enable_categorical=False, eval_metric=None, feature_types=None,\n             gamma=None, grow_policy=None, importance_type=None,\n             interaction_constraints=None, learning_rate=None, max_bin=None,\n             max_cat_threshold=None, max_cat_to_onehot=None,\n             max_delta_step=None, max_depth=None, max_leaves=None,\n             min_child_weight=None, missing=nan, monotone_constraints=None,\n             multi_strategy=None, n_estimators=None, n_jobs=-1,\n             num_parallel_tree=None, random_state=None, ...)","text/html":"<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>XGBRegressor(base_score=None, booster=None, callbacks=None,\n             colsample_bylevel=None, colsample_bynode=None,\n             colsample_bytree=None, device=None, early_stopping_rounds=None,\n             enable_categorical=False, eval_metric=None, feature_types=None,\n             gamma=None, grow_policy=None, importance_type=None,\n             interaction_constraints=None, learning_rate=None, max_bin=None,\n             max_cat_threshold=None, max_cat_to_onehot=None,\n             max_delta_step=None, max_depth=None, max_leaves=None,\n             min_child_weight=None, missing=nan, monotone_constraints=None,\n             multi_strategy=None, n_estimators=None, n_jobs=-1,\n             num_parallel_tree=None, random_state=None, ...)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">XGBRegressor</label><div class=\"sk-toggleable__content\"><pre>XGBRegressor(base_score=None, booster=None, callbacks=None,\n             colsample_bylevel=None, colsample_bynode=None,\n             colsample_bytree=None, device=None, early_stopping_rounds=None,\n             enable_categorical=False, eval_metric=None, feature_types=None,\n             gamma=None, grow_policy=None, importance_type=None,\n             interaction_constraints=None, learning_rate=None, max_bin=None,\n             max_cat_threshold=None, max_cat_to_onehot=None,\n             max_delta_step=None, max_depth=None, max_leaves=None,\n             min_child_weight=None, missing=nan, monotone_constraints=None,\n             multi_strategy=None, n_estimators=None, n_jobs=-1,\n             num_parallel_tree=None, random_state=None, ...)</pre></div></div></div></div></div>"},"metadata":{}}]},{"cell_type":"code","source":"pred_valid_y = model.predict(valid_x)\npred_valid_y","metadata":{"execution":{"iopub.status.busy":"2024-05-21T13:34:53.927856Z","iopub.execute_input":"2024-05-21T13:34:53.928285Z","iopub.status.idle":"2024-05-21T13:34:54.170011Z","shell.execute_reply.started":"2024-05-21T13:34:53.928254Z","shell.execute_reply":"2024-05-21T13:34:54.168858Z"},"trusted":true},"execution_count":11,"outputs":[{"execution_count":11,"output_type":"execute_result","data":{"text/plain":"array([0.5309435 , 0.499558  , 0.47337818, ..., 0.54182374, 0.4870788 ,\n       0.6563196 ], dtype=float32)"},"metadata":{}}]},{"cell_type":"code","source":"valid_scores = r2_score(valid_y, pred_valid_y)\nvalid_scores","metadata":{"execution":{"iopub.status.busy":"2024-05-21T13:34:54.171757Z","iopub.execute_input":"2024-05-21T13:34:54.172551Z","iopub.status.idle":"2024-05-21T13:34:54.184516Z","shell.execute_reply.started":"2024-05-21T13:34:54.172510Z","shell.execute_reply":"2024-05-21T13:34:54.183435Z"},"trusted":true},"execution_count":12,"outputs":[{"execution_count":12,"output_type":"execute_result","data":{"text/plain":"0.8082966970366466"},"metadata":{}}]},{"cell_type":"markdown","source":"# linear model","metadata":{}},{"cell_type":"code","source":"from sklearn import linear_model\nmodel = linear_model.Ridge(alpha=0.01) \nmodel.fit(train_x,train_y)\n\nmodel","metadata":{"execution":{"iopub.status.busy":"2024-05-21T13:34:54.186373Z","iopub.execute_input":"2024-05-21T13:34:54.187221Z","iopub.status.idle":"2024-05-21T13:34:54.529366Z","shell.execute_reply.started":"2024-05-21T13:34:54.187169Z","shell.execute_reply":"2024-05-21T13:34:54.527703Z"},"trusted":true},"execution_count":13,"outputs":[{"execution_count":13,"output_type":"execute_result","data":{"text/plain":"Ridge(alpha=0.01)","text/html":"<style>#sk-container-id-2 {color: black;background-color: white;}#sk-container-id-2 pre{padding: 0;}#sk-container-id-2 div.sk-toggleable {background-color: white;}#sk-container-id-2 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-2 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-2 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-2 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-2 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-2 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-2 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-2 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-2 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-2 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-2 div.sk-item {position: relative;z-index: 1;}#sk-container-id-2 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-2 div.sk-item::before, #sk-container-id-2 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-2 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-2 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-2 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-2 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-2 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-2 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-2 div.sk-label-container {text-align: center;}#sk-container-id-2 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-2 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Ridge(alpha=0.01)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">Ridge</label><div class=\"sk-toggleable__content\"><pre>Ridge(alpha=0.01)</pre></div></div></div></div></div>"},"metadata":{}}]},{"cell_type":"code","source":"model.n_features_in_","metadata":{"execution":{"iopub.status.busy":"2024-05-21T13:34:54.531039Z","iopub.execute_input":"2024-05-21T13:34:54.531453Z","iopub.status.idle":"2024-05-21T13:34:54.543097Z","shell.execute_reply.started":"2024-05-21T13:34:54.531410Z","shell.execute_reply":"2024-05-21T13:34:54.539444Z"},"trusted":true},"execution_count":14,"outputs":[{"execution_count":14,"output_type":"execute_result","data":{"text/plain":"20"},"metadata":{}}]},{"cell_type":"code","source":"pred_valid_y = model.predict(valid_x)\npred_valid_y= pred_valid_y.flatten()\npred_valid_y","metadata":{"execution":{"iopub.status.busy":"2024-05-21T13:34:54.544822Z","iopub.execute_input":"2024-05-21T13:34:54.545566Z","iopub.status.idle":"2024-05-21T13:34:54.590356Z","shell.execute_reply.started":"2024-05-21T13:34:54.545528Z","shell.execute_reply":"2024-05-21T13:34:54.588846Z"},"trusted":true},"execution_count":15,"outputs":[{"execution_count":15,"output_type":"execute_result","data":{"text/plain":"array([0.53983958, 0.49450513, 0.47168639, ..., 0.5394258 , 0.48887536,\n       0.64685272])"},"metadata":{}}]},{"cell_type":"code","source":"valid_scores = r2_score(valid_y, pred_valid_y)\nvalid_scores","metadata":{"execution":{"iopub.status.busy":"2024-05-21T13:34:54.597571Z","iopub.execute_input":"2024-05-21T13:34:54.601462Z","iopub.status.idle":"2024-05-21T13:34:54.625526Z","shell.execute_reply.started":"2024-05-21T13:34:54.601404Z","shell.execute_reply":"2024-05-21T13:34:54.624060Z"},"trusted":true},"execution_count":16,"outputs":[{"execution_count":16,"output_type":"execute_result","data":{"text/plain":"0.843773546037808"},"metadata":{}}]},{"cell_type":"code","source":"import lightgbm\n\nmodel = lightgbm.LGBMRegressor(n_jobs=-1,max_depth=10, num_leaves=50)\nmodel.fit(train_x, train_y)\npred_valid_y = model.predict(valid_x)\npred_valid_y= pred_valid_y.flatten()\npred_valid_y\nvalid_scores = r2_score(valid_y, pred_valid_y)\nvalid_scores","metadata":{"execution":{"iopub.status.busy":"2024-05-21T13:34:54.632437Z","iopub.execute_input":"2024-05-21T13:34:54.636273Z","iopub.status.idle":"2024-05-21T13:35:08.156548Z","shell.execute_reply.started":"2024-05-21T13:34:54.636200Z","shell.execute_reply":"2024-05-21T13:35:08.155462Z"},"trusted":true},"execution_count":17,"outputs":[{"name":"stdout","text":"[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.128734 seconds.\nYou can set `force_col_wise=true` to remove the overhead.\n[LightGBM] [Info] Total Bins 348\n[LightGBM] [Info] Number of data points in the train set: 894365, number of used features: 20\n[LightGBM] [Info] Start training from score 0.504487\n","output_type":"stream"},{"execution_count":17,"output_type":"execute_result","data":{"text/plain":"0.7836837384615066"},"metadata":{}}]},{"cell_type":"markdown","source":"# orig test data prediction","metadata":{}},{"cell_type":"code","source":"test_x = orig_test.copy()\ntest_x.head()","metadata":{"execution":{"iopub.status.busy":"2024-05-21T13:35:08.157824Z","iopub.execute_input":"2024-05-21T13:35:08.158374Z","iopub.status.idle":"2024-05-21T13:35:08.220937Z","shell.execute_reply.started":"2024-05-21T13:35:08.158342Z","shell.execute_reply":"2024-05-21T13:35:08.219650Z"},"trusted":true},"execution_count":18,"outputs":[{"execution_count":18,"output_type":"execute_result","data":{"text/plain":"         MonsoonIntensity  TopographyDrainage  RiverManagement  Deforestation  \\\nid                                                                              \n1117957                 4                   6                3              5   \n1117958                 4                   4                2              9   \n1117959                 1                   3                6              5   \n1117960                 2                   4                4              6   \n1117961                 6                   3                2              4   \n\n         Urbanization  ClimateChange  DamsQuality  Siltation  \\\nid                                                             \n1117957             6              7            8          7   \n1117958             5              5            4          7   \n1117959             7              2            4          6   \n1117960             4              5            4          3   \n1117961             6              4            5          5   \n\n         AgriculturalPractices  Encroachments  \\\nid                                              \n1117957                      8              4   \n1117958                      5              4   \n1117959                      4              2   \n1117960                      4              4   \n1117961                      3              7   \n\n         IneffectiveDisasterPreparedness  DrainageSystems  \\\nid                                                          \n1117957                                8                5   \n1117958                                2                4   \n1117959                                7                9   \n1117960                                7                8   \n1117961                                4                3   \n\n         CoastalVulnerability  Landslides  Watersheds  \\\nid                                                      \n1117957                     7           5           6   \n1117958                     7           4           5   \n1117959                     2           5           5   \n1117960                     4           6           7   \n1117961                     2           6           4   \n\n         DeterioratingInfrastructure  PopulationScore  WetlandLoss  \\\nid                                                                   \n1117957                            3                6            4   \n1117958                            1                7            4   \n1117959                            2                3            6   \n1117960                            6                4            2   \n1117961                            6                8            4   \n\n         InadequatePlanning  PoliticalFactors  \nid                                             \n1117957                   4                 5  \n1117958                   4                 3  \n1117959                   8                 3  \n1117960                   4                 4  \n1117961                   5                 5  ","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>MonsoonIntensity</th>\n      <th>TopographyDrainage</th>\n      <th>RiverManagement</th>\n      <th>Deforestation</th>\n      <th>Urbanization</th>\n      <th>ClimateChange</th>\n      <th>DamsQuality</th>\n      <th>Siltation</th>\n      <th>AgriculturalPractices</th>\n      <th>Encroachments</th>\n      <th>IneffectiveDisasterPreparedness</th>\n      <th>DrainageSystems</th>\n      <th>CoastalVulnerability</th>\n      <th>Landslides</th>\n      <th>Watersheds</th>\n      <th>DeterioratingInfrastructure</th>\n      <th>PopulationScore</th>\n      <th>WetlandLoss</th>\n      <th>InadequatePlanning</th>\n      <th>PoliticalFactors</th>\n    </tr>\n    <tr>\n      <th>id</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>1117957</th>\n      <td>4</td>\n      <td>6</td>\n      <td>3</td>\n      <td>5</td>\n      <td>6</td>\n      <td>7</td>\n      <td>8</td>\n      <td>7</td>\n      <td>8</td>\n      <td>4</td>\n      <td>8</td>\n      <td>5</td>\n      <td>7</td>\n      <td>5</td>\n      <td>6</td>\n      <td>3</td>\n      <td>6</td>\n      <td>4</td>\n      <td>4</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>1117958</th>\n      <td>4</td>\n      <td>4</td>\n      <td>2</td>\n      <td>9</td>\n      <td>5</td>\n      <td>5</td>\n      <td>4</td>\n      <td>7</td>\n      <td>5</td>\n      <td>4</td>\n      <td>2</td>\n      <td>4</td>\n      <td>7</td>\n      <td>4</td>\n      <td>5</td>\n      <td>1</td>\n      <td>7</td>\n      <td>4</td>\n      <td>4</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>1117959</th>\n      <td>1</td>\n      <td>3</td>\n      <td>6</td>\n      <td>5</td>\n      <td>7</td>\n      <td>2</td>\n      <td>4</td>\n      <td>6</td>\n      <td>4</td>\n      <td>2</td>\n      <td>7</td>\n      <td>9</td>\n      <td>2</td>\n      <td>5</td>\n      <td>5</td>\n      <td>2</td>\n      <td>3</td>\n      <td>6</td>\n      <td>8</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>1117960</th>\n      <td>2</td>\n      <td>4</td>\n      <td>4</td>\n      <td>6</td>\n      <td>4</td>\n      <td>5</td>\n      <td>4</td>\n      <td>3</td>\n      <td>4</td>\n      <td>4</td>\n      <td>7</td>\n      <td>8</td>\n      <td>4</td>\n      <td>6</td>\n      <td>7</td>\n      <td>6</td>\n      <td>4</td>\n      <td>2</td>\n      <td>4</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>1117961</th>\n      <td>6</td>\n      <td>3</td>\n      <td>2</td>\n      <td>4</td>\n      <td>6</td>\n      <td>4</td>\n      <td>5</td>\n      <td>5</td>\n      <td>3</td>\n      <td>7</td>\n      <td>4</td>\n      <td>3</td>\n      <td>2</td>\n      <td>6</td>\n      <td>4</td>\n      <td>6</td>\n      <td>8</td>\n      <td>4</td>\n      <td>5</td>\n      <td>5</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"\npred_test_x = model.predict(test_x)\npred_test_x","metadata":{"execution":{"iopub.status.busy":"2024-05-21T13:35:08.222500Z","iopub.execute_input":"2024-05-21T13:35:08.222993Z","iopub.status.idle":"2024-05-21T13:35:15.854368Z","shell.execute_reply.started":"2024-05-21T13:35:08.222954Z","shell.execute_reply":"2024-05-21T13:35:15.853231Z"},"trusted":true},"execution_count":19,"outputs":[{"execution_count":19,"output_type":"execute_result","data":{"text/plain":"array([0.56673039, 0.4690567 , 0.47001233, ..., 0.59631509, 0.54175041,\n       0.50720669])"},"metadata":{}}]},{"cell_type":"markdown","source":"# submission df","metadata":{}},{"cell_type":"code","source":"submission_df = pd.DataFrame()\nsubmission_df['id'] = test_x.index\nsubmission_df['FloodProbability'] = np.around(pred_test_x,1)\nsubmission_df.head()","metadata":{"execution":{"iopub.status.busy":"2024-05-21T13:35:15.855644Z","iopub.execute_input":"2024-05-21T13:35:15.855980Z","iopub.status.idle":"2024-05-21T13:35:15.892911Z","shell.execute_reply.started":"2024-05-21T13:35:15.855952Z","shell.execute_reply":"2024-05-21T13:35:15.891818Z"},"trusted":true},"execution_count":20,"outputs":[{"execution_count":20,"output_type":"execute_result","data":{"text/plain":"        id  FloodProbability\n0  1117957               0.6\n1  1117958               0.5\n2  1117959               0.5\n3  1117960               0.5\n4  1117961               0.5","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>id</th>\n      <th>FloodProbability</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1117957</td>\n      <td>0.6</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1117958</td>\n      <td>0.5</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1117959</td>\n      <td>0.5</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1117960</td>\n      <td>0.5</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1117961</td>\n      <td>0.5</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"submission_df.to_csv('submission.csv',index=False)","metadata":{"execution":{"iopub.status.busy":"2024-05-21T13:35:15.894223Z","iopub.execute_input":"2024-05-21T13:35:15.894562Z","iopub.status.idle":"2024-05-21T13:35:17.339012Z","shell.execute_reply.started":"2024-05-21T13:35:15.894534Z","shell.execute_reply":"2024-05-21T13:35:17.337808Z"},"trusted":true},"execution_count":21,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}