readme: ---
  library_name: sklearn
  tags:
  - sklearn
  - skops
  - tabular-regression
  widget:
    structuredData:
      AveBedrms:
      - 0.9806451612903225
      - 1.0379746835443038
      - 0.9601449275362319
      AveOccup:
      - 2.587096774193548
      - 2.8658227848101268
      - 2.6449275362318843
      AveRooms:
      - 7.275268817204301
      - 5.39493670886076
      - 6.536231884057971
      HouseAge:
      - 38.0
      - 25.0
      - 39.0
      Latitude:
      - 37.44
      - 37.31
      - 34.16
      Longitude:
      - -122.19
      - -122.03
      - -118.07
      MedInc:
      - 9.3198
      - 5.3508
      - 6.4761
      Population:
      - 1203.0
      - 1132.0
      - 730.0
  ---
  
  # Model description
  
  [More Information Needed]
  
  ## Intended uses & limitations
  
  [More Information Needed]
  
  ## Training Procedure
  
  ### Hyperparameters
  
  The model is trained with below hyperparameters.
  
  <details>
  <summary> Click to expand </summary>
  
  | Hyperparameter           | Value         |
  |--------------------------|---------------|
  | bootstrap                | True          |
  | ccp_alpha                | 0.0           |
  | criterion                | squared_error |
  | max_depth                |               |
  | max_features             | 1.0           |
  | max_leaf_nodes           |               |
  | max_samples              |               |
  | min_impurity_decrease    | 0.0           |
  | min_samples_leaf         | 1             |
  | min_samples_split        | 2             |
  | min_weight_fraction_leaf | 0.0           |
  | n_estimators             | 100           |
  | n_jobs                   |               |
  | oob_score                | False         |
  | random_state             |               |
  | verbose                  | 0             |
  | warm_start               | False         |
  
  </details>
  
  ### Model Plot
  
  The model plot is below.
  
  <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-w