Supervised Learning

In supervised learning, we are given an input (some data set) and an output. There is some relationship between the input and output.

Supervised learning problems are classified into:

  1. regression and
  2. classification problems.

In a regression problem, we try to predict results by mapping input variables to some continuous output function.

e.g., trying to predict housing prices given a set of house sizes and their respective prices

In a classification problem, we try to predict results by mapping input variables into discrete categories.

e.g., trying to predict whether a tumor is malignant or benign given a patient with a tumor

Published November 28, 2016