By design, SVM algorithms are binary classifiers. However, there are a few strategies employed to get them to work on multiple classes. The two main strategies are called One versus all, and One versus one.
One versus one is a strategy where a binary classifier is created for each possible pair of classes. Then, a prediction is made for a point for the class that has the most votes. This can be computationally hard, as we must create 
classifiers for k classes.
Another way to implement multi-class classifiers is to do a one versus all strategy where we create a classifier for each of theclasses. The predicted class of a point ...
