Data Science, Machine Learning, Support Vector Machine, Python.
even when the data is not linearly separable. After finding the hyperplane, it is possible to classify new, unseen data by input the points into the SVM. It will predict to which side of the hyperplane the data belongs to based on its position in the feature space. To recapitulate, SVMs work by