README.md

metadata

license: mit
library_name: sklearn
tags:
  - sklearn
  - skops
  - tabular-classification
model_format: pickle
model_file: breast.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
        - 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
        - 1156
      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

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
monotonic_cst
random_state
splitter	best

Model Plot

DecisionTreeClassifier()

In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.

Evaluation Results

Metric	Value
accuracy	0.947368
f1 score	0.947368

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