Python Machine Learning By Example - Fourth Edition

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Recognizing Faces with Support Vector Machine

In the previous chapter, we discovered underlying topics using clustering and topic modeling techniques. This chapter continues our journey of supervised learning and classification, with a particular emphasis on Support Vector Machine (SVM) classifiers.

SVM is one of the most popular algorithms when it comes to high-dimensional spaces. The goal of the algorithm is to find a decision boundary in order to separate data from different classes. We will discuss in detail how that works. Also, we will implement the algorithm with scikit-learn and apply it to solve various real-life problems, including our main project of face recognition. A dimensionality reduction technique called principal component ...