In this tutorial we will talk in brief about a class of Machine learning problems – Classification Problems. We will try to establish the concept of classification and why they are so important.
In this series of articles so far we have seen Basics of machine learning, Linearity of Regression problems , Construct of Linear regression and 2 variable as well as multiple linear regression. Just to revise Linear regression can be used when we have our response variable ( aka. dependent variable ) as a continuous variable.
In most of the problems in machine learning however we want to predict whether our output variable belongs to a particular category.
- Amazon wants to know whether a cash on delivery order be accepted by a customer or not when delivered ( Yes or No )
- Bank of America wants to know if a customer will pay back the loan on time , Prepay or not pay at all ( OnTime Or Prepaid or Default )
- Doctors want to know whether a patient will develop Coronary Heart Disease within next 10 years or not ( Yes or No )
- Optical Character Reader wants to read English Characters and find which character is read ( A or B or C – Z or 1 or 2 or 3 -9 )
All of these are classification problems which fall under the area of Supervised Learning.
Problem 1 and Problem 3 in RED are Binary classification problems since we are classifying the output into 2 classes in both the cases as Yes or No.
Problem 2 and Problem 4 in BLUE are Multi Class Classification problems since we want to classify output into more than one classes.
Following techniques are popular for Binary Classification problems.
a. Logistic Regression
b. Decision Trees
c. Random Forests
d. Neural Networks
e. Support Vector Machines
Multi Class Classification
Multi class classification problems are popularly tackled using following techniques.
a. Multinomial Logistic Regression
b. Support Vector Machines
c. Neural Networks
d. A popular technique is to split a multi class classification problem into multiple binary classification problems and then then model each of the sub problem separately.
We will learn and examine most of these classification techniques in subsequent posts , till then Happy Learning !