What are the two classification methods that SVM ( Support Vector Machine) can handle?

by
  • Combining binary classifiers
  • Modifying binary to incorporate multiclass learning

The two classification methods that Support Vector Machine (SVM) can handle are:

  1. Binary Classification: SVM is primarily used for binary classification tasks, where the goal is to classify data points into one of two categories.
  2. Multi-class Classification: SVM can also be extended to handle multi-class classification problems through techniques like One-vs-All (OvA) or One-vs-One (OvO) strategies. In OvA, a separate SVM classifier is trained for each class, treating it as the positive class and the rest as the negative class. In OvO, SVM classifiers are trained for each pair of classes, and the class with the most votes is chosen as the final prediction.