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Regression
Regression is one of the oldest tools for mathematical modeling, classification, and
prediction, yet remains quite a powerful one. Regression finds application in varied
fields ranging from engineering, physical science, biology, and the financial market,
to the social sciences. It is a fundamental tool in the hands of statisticians and data
scientists. In this chapter, we will cover the following topics:
• Linear regression
• Different types of linear regression
• Logistic regression
• Apply linear regression to estimate the price of a house
• Apply logistic regression to identify handwritten digits
Let us first start with understanding what regression really is.
What is regression?
Regression is normally the first algorithm that people in machine learning work
with. It allows us to make predictions from data by learning about the relationship
between a given set of dependent and independent variables. It has its use in almost
every field; anywhere that has an interest in drawing relationships between two or
more things will find a use for regression.
Consider the case of house price estimation. There are many factors that can have
an impact on the house price: the number of rooms, the floor area, the locality, the
availability of amenities, the parking space, and so on. Regression analysis can
help us in finding the mathematical relationship between these factors and the
house price.
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