forge_classify_svm

forge_classify_svm, a scikit-learn code which uses the support vector algorithm to choose one of two classes for each of 26 items in the forge dataset, involving two features.

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:

blob_classify_kernelized_svm, a scikit-learn code which uses a kernelized support vector machine to classify an artificial dataset of groups of "blobs".

forge_classify_knn, a scikit-learn code which uses the k-nearest neighbor algorithm 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.

Reference:

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

Source Code:

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

• forge_classify_svm_0.01.png, shows the decision boundary with c = 0.01.
• forge_classify_svm_10.0.png, shows the decision boundary with c = 10.
• forge_classify_svm_1000.0.png, shows the decision boundary with c = 1000.