cancer_classify_gradboost

cancer_classify_gradboost, a scikit-learn code which uses the gradient boosting algorithm to classify the breast cancer dataset.

Licensing:

The computer code and data files described and made available on this web page are distributed under the MIT license

Related Data and Programs:

cancer_classify_decision, a scikit-learn code which uses a decision tree algorithm on the breast cancer dataset, comparing the training and testing accuracy as the depth of the tree is varied.

cancer_classify_forest, a scikit-learn code which uses the random forest algorithm on the breast cancer dataset.

cancer_classify_knn, a scikit-learn code which uses the k-nearest neighbor algorithm on the breast cancer dataset, comparing the training and testing accuracy as the number of neighbors is increased.

cancer_classify_logistic, a scikit-learn code which uses logistic regression on the breast cancer dataset, investigating the influence of the C parameter.

Reference:

• Andreas Mueller, Sarah Guido,
  Introduction to Machine Learning with Python,
  OReilly, 2017,
  ISBN: 978-1-449-36941-5

Source Code:

• cancer_classify_gradboost.py, the source code.
• cancer_classify_gradboost.sh, runs the script.
• cancer_classify_gradboost.txt, the output file.

• cancer_classify_gradboost.png, shows the feature importance ratings.