3 Supervised Learning - Supervised Learning
Supervised learning means that first some dataset needs to be provided and for each data in the dataset, there is a corresponding correct answer and the (training set) algorithm is making predictions based on these correct answers. It is further divided into regression problems and classification problems.
1.Regression problems: predicting a continuous output value by regression.
2.Classification problem: Predicting the output of a discrete value by classification.
Given data about the size of houses on the real estate market, try to predict their price. Price
as a function of size is a continuous output, so this is a regression problem.
We could turn this example into a classification problem by instead making our output about
whether the house "sells for more or less than the asking price." Here we are classifying the
houses based on price into two discrete categories.