Model training is the phase in which a machine learning algorithm learns from the data in hand. The learning algorithm detects data patterns and relationships, and categorizes data into classes. The data attributes need to be properly sampled to attain the best performance from the models. Usually 70-80 percent of the data is used in the training phase.