Support Vector Machine, Support Vector Regression, Support Vector Classifier, Support Vectors, Machine Learning.
each class. SVM is particularly useful for datasets with a large number of features, as it can handle high-dimensional data effectively. It can also handle non-linearly separable data by using kernel functions to map the input data to a higher-dimensional space where it can be linearly separated.