--- license: mit library_name: sklearn tags: - sklearn - skops - tabular-classification model_format: pickle model_file: example.pkl widget: - structuredData: area error: - 30.29 - 96.05 - 48.31 compactness error: - 0.01911 - 0.01652 - 0.01484 concave points error: - 0.01037 - 0.0137 - 0.01093 concavity error: - 0.02701 - 0.02269 - 0.02813 fractal dimension error: - 0.003586 - 0.001698 - 0.002461 mean area: - 481.9 - 1130.0 - 748.9 mean compactness: - 0.1058 - 0.1029 - 0.1223 mean concave points: - 0.03821 - 0.07951 - 0.08087 mean concavity: - 0.08005 - 0.108 - 0.1466 mean fractal dimension: - 0.06373 - 0.05461 - 0.05796 mean perimeter: - 81.09 - 123.6 - 101.7 mean radius: - 12.47 - 18.94 - 15.46 mean smoothness: - 0.09965 - 0.09009 - 0.1092 mean symmetry: - 0.1925 - 0.1582 - 0.1931 mean texture: - 18.6 - 21.31 - 19.48 perimeter error: - 2.497 - 5.486 - 3.094 radius error: - 0.3961 - 0.7888 - 0.4743 smoothness error: - 0.006953 - 0.004444 - 0.00624 symmetry error: - 0.01782 - 0.01386 - 0.01397 texture error: - 1.044 - 0.7975 - 0.7859 worst area: - 677.9 - 1866.0 - 1156.0 worst compactness: - 0.2378 - 0.2336 - 0.2394 worst concave points: - 0.1015 - 0.1789 - 0.1514 worst concavity: - 0.2671 - 0.2687 - 0.3791 worst fractal dimension: - 0.0875 - 0.06589 - 0.08019 worst perimeter: - 96.05 - 165.9 - 124.9 worst radius: - 14.97 - 24.86 - 19.26 worst smoothness: - 0.1426 - 0.1193 - 0.1546 worst symmetry: - 0.3014 - 0.2551 - 0.2837 worst texture: - 24.64 - 26.58 - 26.0 --- # Model description [More Information Needed] ## Intended uses & limitations [More Information Needed] ## Training Procedure [More Information Needed] ### Hyperparameters
Click to expand | Hyperparameter | Value | |--------------------------|---------| | ccp_alpha | 0.0 | | class_weight | | | criterion | gini | | max_depth | | | max_features | | | max_leaf_nodes | | | min_impurity_decrease | 0.0 | | min_samples_leaf | 1 | | min_samples_split | 2 | | min_weight_fraction_leaf | 0.0 | | random_state | | | splitter | best |
### Model Plot
DecisionTreeClassifier()
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## Evaluation Results | Metric | Value | |----------|----------| | accuracy | 0.923977 | | f1 score | 0.923977 | # 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={2020}} # get_started_code import pickle with open(dtc_pkl_filename, 'rb') as file: clf = pickle.load(file) # model_card_authors skops_user # limitations This model is not ready to be used in production. # model_description This is a DecisionTreeClassifier model trained on breast cancer 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)