--- license: mit library_name: sklearn tags: - sklearn - skops - tabular-classification model_format: pickle model_file: rf_model.pkl widget: structuredData: x0: - 22353.0 - 18097.0 - 1893.0 x1: - 300.0 - 0.0 - 0.0 x10: - 6.0 - 6.0 - 6.0 x11: - 14.300000190734863 - 18.0 - 12.5 x12: - 0.0 - 0.0 - 0.0 x13: - -0.1458740234375 - -0.016845703125 - -0.145751953125 x14: - 2574.0 - 2243.0 - 2393.0 x2: - 1376.530029296875 - 1810.1199951171875 - 284.42999267578125 x3: - 0.0 - 0.0 - 0.0 x4: - 0.0 - 0.0 - 0.0 x5: - 0.0 - 126.66000366210938 - 19.809999465942383 x6: - 44.311378479003906 - 40.6067008972168 - 44.311378479003906 x7: - 0.0 - 0.0 - 0.0 x8: - 29.5 - 27.0 - 9.399999618530273 x9: - 1.0 - 1.0 - 1.0 --- # 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 | | class_weight | | | criterion | gini | | max_depth | | | max_features | sqrt | | 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 | 25 | | n_jobs | -1 | | oob_score | False | | random_state | 1 | | verbose | 0 | | warm_start | False |
### Model Plot The model plot is below.
RandomForestClassifier(n_estimators=25, n_jobs=-1, random_state=1)
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## Evaluation Results You can find the details about evaluation process and the evaluation results. | Metric | Value | |----------|----------| | accuracy | 0.988057 | | f1 score | 0.988057 | # 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] ``` # citation_bibtex bibtex @inproceedings{...,year={2023}} # get_started_code import pickle with open(dtc_pkl_filename, 'rb') as file: clf = pickle.load(file) # model_card_authors Marvin Lomo # limitations This model is not ready to be used in production. # model_description This is a RandomForrestClassifier model trained on SME Churn Dataset. # eval_method The model is evaluated using test split, on accuracy and F1 score with macro average. # confusion_matrix ![confusion_matrix](confusion_matrix.png)