What is Supervised Learning?

Data Science, AI and ML
1

Supervised learning is a machine learning algorithm of inferring a function from labeled training data. The training data consists of a set of training examples.

Example: 01

Knowing the height and weight identifying the gender of the person. Below are the popular supervised learning algorithms.

  • Support Vector Machines
  • Regression
  • Naive Bayes
  • Decision Trees
  • K-nearest Neighbour Algorithm and Neural Networks.

Example: 02

If you build a T-shirt classifier, the labels will be “this is an S, this is an M and this is L”, based on showing the classifier examples of S, M, and L.

2

Supervised Learning, involves taking p+1 measurements of n individuals. Out of those p+1 variables, we nominate one of the variables as target variables and predict it’s future value with the help of the remaining p variables (called predictors/explanatory variables).

If our target variable happens to be categorical, then it means we are doing classification and if our target variable happens to be numeric, then it means we are doing regression.