--- library_name: sklearn tags: - sklearn - skops - tabular-classification model_format: pickle model_file: model.pkl widget: - structuredData: blue_aggressiveness_score: - 1.292 - 1.0 - 1.115 blue_avg_durability: - 4.8 - 5.2 - 5.2 blue_avg_offense: - 6.2 - 5.2 - 5.8 blue_early_mid_ratio: - 1.0 - 0.667 - 1.5 blue_mid_late_ratio: - 1.5 - 1.5 - 2.0 control_effects_diff: - -22 - 0 - -2 difficulty_diff: - 7 - 0 - 5 durability_diff: - -8 - -11 - 3 offense_diff: - 5 - 6 - 0 power_spike_diff: - -1 - -1 - -3 red_aggressiveness_score: - 0.812 - 0.541 - 1.261 red_avg_durability: - 6.4 - 7.4 - 4.6 red_avg_offense: - 5.2 - 4.0 - 5.8 red_early_mid_ratio: - 1.0 - 1.333 - 0.5 red_mid_late_ratio: - 4.0 - 3.0 - 1.333 --- # Model description This is a RandomForestClassifier model trained on mpl_id_s14 dataset. ## Intended uses & limitations [More Information Needed] ## Training Procedure [More Information Needed] ### Hyperparameters
Click to expand | Hyperparameter | Value | |--------------------------|---------| | bootstrap | True | | ccp_alpha | 0.0 | | class_weight | | | criterion | gini | | max_depth | 2 | | max_features | sqrt | | max_leaf_nodes | | | max_samples | | | min_impurity_decrease | 0.0 | | min_samples_leaf | 8 | | min_samples_split | 2 | | min_weight_fraction_leaf | 0.0 | | monotonic_cst | | | n_estimators | 50 | | n_jobs | | | oob_score | False | | random_state | 91 | | verbose | 0 | | warm_start | False |
### Model Plot
RandomForestClassifier(max_depth=2, min_samples_leaf=8, n_estimators=50,random_state=91)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
## Evaluation Results [More Information Needed] # How to Get Started with the Model [More Information Needed] # Model Card Authors z4fL # 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] ``` # Limitations This model is only trained with MPL ID Season 14 data # confusion_matrix ![confusion_matrix](confusion_matrix.png)