Model description
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Intended uses & limitations
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Training Procedure
Hyperparameters
The model is trained with below hyperparameters.
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| 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
The model plot is below.
DecisionTreeClassifier()In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
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DecisionTreeClassifier()
Evaluation Results
You can find the details about evaluation process and the evaluation results.
| Metric | Value |
|---|---|
| accuracy | 0.94152 |
| f1 score | 0.94152 |
How to Get Started with the Model
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Model Card Authors
This model card is written by following authors:
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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:
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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
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