mahrukhw/DecisissionTreeClassifier

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()

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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