Support Vector Machines and Perceptrons by M.N. Murty & Rashmi Raghava

Author:M.N. Murty & Rashmi Raghava
Language: eng
Format: epub
Publisher: Springer International Publishing, Cham

3.It employs a suitable similarity function in the input space and avoids making expensive computations in the high-dimensional feature space.

4.It combines the training data points to obtain W and use the W for classification .

In its simplest form, the SVM can be used to classify patterns belonging to two classes that are linearly separable .

4.2 Linear SVM [1, 5 ]

Given the training set ,

Let the two classes be linearly separable . This means there is a and a satisfying1.

2.

We can put these two sets of inequalities together to write

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