This tutorial completes the course material devoted to the Support Vector Machine approach (SVM).
It highlights two important dimensions of the method: the position of the support points and the definition of the decision boundaries in the representation space when we construct a linear separator; the difficulty to determine the “best” values of the parameters for a given problem.
We will use R (“e1071” package) and Python (“scikit-learn” package).
Keywords: svm, package e1071, logiciel R, logiciel Python, package scikit-learn, sklearn
Tutorial: SVM - Support Vector Machine
Dataset and programs: svm_r_python.zip
References:
Tanagra Tutorial, "Support Vector Machine", May 2017.
Tanagra Tutorial, "Implementing SVM on large dataset", July 2009.
