Support Vector Machine is a machine learning algorithm used in automatic classification of previously unseen data. In this post I would like to explain how SVM works and where it’s usually used.
In general, machine learning based classification is about learning how to separate two sets of data examples. Basing on this knowledge system can correctly put unseen examples into one of the other set. Spam filter is a very good example of automatic classification system. Let’s imagine a two dimensional space with points, SVM algorithm is about finding a line (hyperplane) that separate points into two classes.
The main idea behind this algorithm is that the gap dividing points should be as wide as it’s possible.