Terminology

From https://www.safaribooksonline.com/library/view/apache-spark-2x/9781787126497/74757d2e-dd20-4d7a-8531-2d31716f091e.xhtml

Machine learning also has some terminologies that are specific to its domain and it is worth discussing them:

• Feature

  : For any observation feature represents a set of traits that describes the entity quantitatively. For example, for a car the feature can be its color, car model, number of seats, and so on.

• Label

  : Label is a dependent entity whose outcome is related to the values of a feature. Such as in case of features of a car depending on the car model and number of seats and the label could be the maker of the car.

Input variables (X): Features, predictors, explanatory variables, independent variables

Output variables (Y): Response variable, dependent variable