Q23. Support vector machines (SVMs) are a set of supervised learning methods used for

1. Linear classification

2. Non-linear classification

3. Regression

4. Only 1 and 3

Ans : 5

Exp: In machine learning, support vector machines (SVMs, also support vector networks[1]) are supervised learning models with associated learning algorithms that analyze data and recognize patterns, used for classification and regression analysis. In addition to performing linear classification, SVMs can efficiently perform a non-linear classification using what is called the kernel trick, implicitly mapping their inputs into high-dimensional feature spaces.