Support Vector Machines (SVMs) are supervised machine learning algorithms used for classification tasks. To use a SVM classifier, the data set is first split into training and test sets. The training data is then used to build a model by finding the hyperplanes that separate the different classes. Finally, the model is tested on the test data to evaluate its accuracy.
Explain how to use an SVM classifier to classify data.