--- library_name: sklearn tags: - sklearn - skops - tabular-classification model_format: pickle model_file: model.pkl widget: - structuredData: found_in_search_area: - true - true - false --- # Model description [More Information Needed] ## Intended uses & limitations [More Information Needed] ## Training Procedure [More Information Needed] ### Hyperparameters
Click to expand | Hyperparameter | Value | |---------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------| | memory | | | steps | [('columntransformer', ColumnTransformer(transformers=[('standardscaler', StandardScaler(),
['location_found_elevation']),
('onehotencoder', OneHotEncoder(),
['situation'])])), ('randomforestclassifier', RandomForestClassifier(class_weight={False: 1.9217032967032968,
True: 0.6758454106280193},
random_state=42))] | | verbose | False | | columntransformer | ColumnTransformer(transformers=[('standardscaler', StandardScaler(),
['location_found_elevation']),
('onehotencoder', OneHotEncoder(),
['situation'])]) | | randomforestclassifier | RandomForestClassifier(class_weight={False: 1.9217032967032968,
True: 0.6758454106280193},
random_state=42) | | columntransformer__n_jobs | | | columntransformer__remainder | drop | | columntransformer__sparse_threshold | 0.3 | | columntransformer__transformer_weights | | | columntransformer__transformers | [('standardscaler', StandardScaler(), ['location_found_elevation']), ('onehotencoder', OneHotEncoder(), ['situation'])] | | columntransformer__verbose | False | | columntransformer__verbose_feature_names_out | True | | columntransformer__standardscaler | StandardScaler() | | columntransformer__onehotencoder | OneHotEncoder() | | columntransformer__standardscaler__copy | True | | columntransformer__standardscaler__with_mean | True | | columntransformer__standardscaler__with_std | True | | columntransformer__onehotencoder__categories | auto | | columntransformer__onehotencoder__drop | | | columntransformer__onehotencoder__dtype | | | columntransformer__onehotencoder__feature_name_combiner | concat | | columntransformer__onehotencoder__handle_unknown | error | | columntransformer__onehotencoder__max_categories | | | columntransformer__onehotencoder__min_frequency | | | columntransformer__onehotencoder__sparse | deprecated | | columntransformer__onehotencoder__sparse_output | True | | randomforestclassifier__bootstrap | True | | randomforestclassifier__ccp_alpha | 0.0 | | randomforestclassifier__class_weight | {False: 1.9217032967032968, True: 0.6758454106280193} | | randomforestclassifier__criterion | gini | | randomforestclassifier__max_depth | | | randomforestclassifier__max_features | sqrt | | randomforestclassifier__max_leaf_nodes | | | randomforestclassifier__max_samples | | | randomforestclassifier__min_impurity_decrease | 0.0 | | randomforestclassifier__min_samples_leaf | 1 | | randomforestclassifier__min_samples_split | 2 | | randomforestclassifier__min_weight_fraction_leaf | 0.0 | | randomforestclassifier__n_estimators | 100 | | randomforestclassifier__n_jobs | | | randomforestclassifier__oob_score | False | | randomforestclassifier__random_state | 42 | | randomforestclassifier__verbose | 0 | | randomforestclassifier__warm_start | False |
### Model Plot 
Pipeline(steps=[('columntransformer',ColumnTransformer(transformers=[('standardscaler',StandardScaler(),['location_found_elevation']),('onehotencoder',OneHotEncoder(),['situation'])])),('randomforestclassifier',RandomForestClassifier(class_weight={False: 1.9217032967032968,True: 0.6758454106280193},random_state=42))])
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## Evaluation Results | Metric | Value | |----------|----------| | accuracy | 0.698333 | | f1_score | 0.698018 | # How to Get Started with the Model [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] ``` # model_description RandomForestClassifier model for tabular classification. # eval_method Evaluated using test split. # confusion_matrix ![confusion_matrix](AI4SAR-model/confusion_matrix.png)