Regression vs. Classification in Machine Learning for Beginners

Decision Tree Classification: This type divides a dataset into segments based on particular feature variables. The divisions' threshold values are typically the mean or mode of the feature variable in question if they happen to be numerical. K-Nearest Neighbors: This Classification type identifies the K nearest neighbors to a given observation point. It then uses K points to evaluate the proportions of each type of target variable and predicts the target variable that has the highest ratio. Logistic Regression: This classification type isn't complex so it can be easily adopted with minimal training. It predicts the probability of Y being associated with the X input variable.