Question

Analytics question: Describe the relationship between a supervised learning classifier and a set of linear equations.

Answer 1

Linear Algebra is a branch of mathematics dealing with linear equations and linear functions. These are represented by matrices and vectors. To elaborate algebra deals with scalars and LA deals with vectors and matrices i.e. entities, which possess two or more dimensional components. It deals with linear equations and functions.

Linear Algebra is also known as an extension of Algebra.

Supervised learning has an input variable (x) and an output variable (y) and the algorithm is used to learn the mapping function from input to the output. The target is to approximate the mapping function in a manner that when you have new input data (x) you can predict the output (y) for that data.

It is called supervised learning because the process of an algorithm learning from a training data set is considered as a teacher supervising the learning process.

Supervised learning problems are classified as linear regression and classification problems.

Classification is used when the output variable is a category such as blue, green, etc

Linear regression is when the output variable is a real value, such as weights and dollars.

Supervised learning includes decision trees, linear regression, logistic regression support vector machines, and ensemble methods.

To conclude linear regression uses a linear equation in a particular form i.e Y=a+bx (where x is the explanatory variable and y is the dependent variable). The linear regression is a technique used by supervised machine learning algorithms.