![]() The demo concludes by displaying some of the trained model's information. Next, the demo computed an output value for a previously unseen input of (2.5, 3.5, 4.5) and because the computed output is False, the predicted class is whatever label is associated with -1. Support Vector Machine Classification in Action A computed output value of False corresponds to -1 and a computed output value of True corresponds to +1 so you can see the trained model predicted all eight training items correctly. ![]() After the SVM model was trained it was used to compute predicted outputs for the training data. ![]() The demo program creates an SVM using a polynomial kernel. The data is artificial but you can imagine it represents a problem where the goal is to predict if a patient will die (-1) or survive (+1) based on numeric scores of a blood test, a heart test and a lung test. Each item has three predictor values, and the class to predict is encoded as -1 or +1. The demo creates a dummy binary classification problem with just eight training items. The best way to get an idea of what SVMs do is to take a look at the image of a demo program in Figure 1. For example, you can use an SVM to create a model that predicts the sex of a person (male, female) based on their age, annual income, height and weight. A support vector machine (SVM) is a software system that can perform binary classification. ![]()
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