sklearn tabular-classification

Model description

This is a DecisionTreeClassifier model trained on breast cancer dataset.

Intended uses & limitations

This model is not ready to be used in production.

Training Procedure

Hyperparameters

The model is trained with below hyperparameters.

<details> <summary> Click to expand </summary>

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

</details>

Model Plot

The model plot is below.

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See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-7c3e7180-7d07-45af-b2c4-4682b6ba8741 div.sk-text-repr-fallback {display: none;}</style><div id="sk-7c3e7180-7d07-45af-b2c4-4682b6ba8741" class="sk-top-container"><div class="sk-text-repr-fallback"><pre>DecisionTreeClassifier()</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class="sk-container" hidden><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="f10c71c1-4f35-46d5-b90a-c6e06005a09c" type="checkbox" checked><label for="f10c71c1-4f35-46d5-b90a-c6e06005a09c" class="sk-toggleable__label sk-toggleable__label-arrow">DecisionTreeClassifier</label><div class="sk-toggleable__content"><pre>DecisionTreeClassifier()</pre></div></div></div></div></div>

## Evaluation Results

You can find the details about evaluation process and the evaluation results.

Metric Value
accuracy 0.935673
f1 score 0.935673

How to Get Started with the Model

Use the code below to get started with the model.

<details> <summary> Click to expand </summary>

import pickle 
with open(dtc_pkl_filename, 'rb') as file: 
clf = pickle.load(file)

</details>

Model Card Authors

This model card is written by following authors:

skops_user

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:

bibtex
@inproceedings{...,year={2020}}

Confusion Matrix Confusion Matrix