--- 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.
Click to expand | 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 |
### Model Plot The model plot is below.
RandomForestRegressor()
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## Evaluation Results You can find the details about evaluation process and the evaluation results. | Metric | Value | |----------|---------| # How to Get Started with the Model Use the code below to get started with the model.
Click to expand ```python [More Information Needed] ```
# Model Card Authors This model card is written by following authors: [More Information Needed] # Model Card Contact You can contact the model card authors through following channels: [More Information Needed] # Citation Below you can find information related to citation. **BibTeX:** ``` [More Information Needed] ```