Perceptron Vs SVM | Machine Learning

Perceptron Vs SVM | Machine Learning

In the second problem, we have the second classifier which is shown here. The first problem is solved using Perceptron or Artificial Neural Network. The same problem can be solved by using another classifier called Support Vector Machine(SVM). The objective here is to draw a line between the two classes so that the distance between them maximizes. We have two classes and the line can be drawn in either way.
However, finding an optimal point helps to maximize the distance between the two classes and such a model is known as a Support Vector Machine. This helps to classify a class into multiple classes and finding an optimal place not only maximizes the distance between the two classes but also the data points which are pretty close to the middle line, referred to as Support Vectors. This is an important model of Machine Learning.


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