README.md

metadata

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
        - 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
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