Machine Learning Algorithms: Which One to Choose for Your Problem

Supervised learning is the task of inferring a function from labeled training data. By fitting to the labeled training set, we want to find the most optimal model parameters to predict unknown labels on other objects (test set). If the label is a real number, we call the task regression. If the label is from the limited number of values, where these values are unordered, then it's classification. In unsupervised learning we have less information about objects, in particular, the train set is unlabeled.