Mastering Machine Learning for Penetration Testing

Support vector machines

A support vector machine (SVM) is a supervised machine learning model that works by identifying a hyperplane between represented data. The data can be represented in a multidimensional space. Thus, SVMs are widely used in classification models. In an SVM, the hyperplane that best separates the different classes will be used. In some cases, when we have different hyperplanes that separate different classes, identification of the correct one will be performed thanks to something called a margin, or a gap. The margin is the nearest distance between the hyperplanes and the data positions. You can take a look at the following representation to check for the margin:

The hyperplane with the highest gap will be selected. ...