cancer_classify_svm_rbf, a scikit-learn code which uses the support vector algorithm with RBF kernel on the cancer dataset, showing that the data should be rescaled to avoid overfitting.
The computer code and data files described and made available on this web page are distributed under the MIT license
blob_classify_kernelized_svm, a scikit-learn code which uses a kernelized support vector machine to classify an artificial dataset of groups of "blobs".
cancer_classify_decision, a scikit-learn code which uses a decision tree algorithm to classify 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 to classify the breast cancer dataset.
cancer_classify_gradboost, a scikit-learn code which uses the gradient boosting algorithm to classify the breast cancer dataset.
cancer_classify_knn, a scikit-learn code which uses the k-nearest neighbor algorithm to classify 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 to classify the breast cancer dataset, investigating the influence of the C parameter.
forge_classify_svm, a scikit-learn code which uses the support vector machine (SVM) classifier to choose one of two classes for each of 26 items in the forge dataset, involving two features.
handcrafted_classify_svm_rbf, a scikit-learn code which uses the support vector algorithm with RBF kernel on the handcrafted dataset.
