Basic Classification and Machine Learning

Basic Classification and Machine Learning

Introduction

As we all know, the regression and classification algorithms are two types of supervised machine Learning algorithms. Regression algorithms are used for predicting the the output for continuous values, but if we want to predict categorical values, a classification algorithm is required.

Classification is the process of dividing a set of data into categories. The primary objective of all classification algorithms is to determine which category or class new data will belong to. Some examples of classification include: detecting if an email is spam or not, detecting the breed of the dog, sentiment analysis, etc.

In terms of modeling, classification demands a training dataset with a large number of instances of inputs and outputs to learn from. There exist various classification algorithms that are being used for solving different tasks and problems. In this tutorial, we’ll tackle the basic ideas behind the most popular and commonly utilized methods.