January 2018
Beginner to intermediate
412 pages
9h 33m
English
Content preview from Practical Big Data Analytics
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Regression models
Regression models range from commonly used linear, logistic, and multiple regression algorithms used in statistics to Ridge and Lasso regression, which penalizes co-efficients to improve model performance.
In our earlier examples, we saw the application of linear regression when we created trend-lines. Multiple linear regression refers to the fact that the process of creating the model requires multiple independent variables.
For instance:
Total Advertising Cost = x* Print Ads, would be a simple linear regression; whereas
Total Advertising Cost = X + Print Ads + Radio Ads + TV Ads, due to the presence of more than one independent variable (Print, Radio, and TV), would be a multiple linear regression.
Logistic regression ...
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