Linear regression :

The link between one or more predictor variables and one outcome variable is quantified by linear regression.

Predictive analysis and modeling frequently use linear regression.

It can be used, for instance, to measure the proportional effects of nutrition, age, and gender (the predictor variables) on height (the outcome variable).

two types :

1. Simple linear regression

2.Multivariante linear regression

 

Simple linear regression :

involves only one variable dependent prediction

Y=mx+b

 

 

                                                       

Download. Houseprice csv file.                                     Download. Houses areas csv file.

 

 

 

Codeblock E.1. Linear regression demo.

 

Exercise to predict canada's precapita income :

Download. Canada per capita income csv file.

 

Solution :

 

Codeblock E.2. Canada prediction for percapita income for years 2020,2022,2023 demo.

 

Multivariante linear regression

Involves multiple variables to predict an output.

Y=m₁x₁+m₂x₂+m₃x₃+bias

 

Download. Houseprices csv file.   

 

Figure E.1. predict the prices for these values.

 

 

Codeblock E.3. Price prediction for houses as seen from the table shown.

 

Exercise to predict the salaries of individuals based on 3 feature vectors.

 

Download. Hiring csv file.

 

Figure E.2. predict the salaries for these values.

 

 

Codeblock E.3. Salary prediction for houses as seen from the table shown.

 

 

---- Summary ----

As of now you know all basics of Protein Structures.

• Linear regression

• Y=mx +b.

• intercept.

• Slope.

• etc..

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