O'Reilly logo

MATLAB for Machine Learning by Giuseppe Ciaburro

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Reducing outlier effects with robust regression

When we use the fitlm() function to create a linear model, we can specify the model type. The model specification you give is the model that is fit. If we do not give a model specification, through the parameters of the function, the linear specification will be adopted by default. A linear model contains an intercept and linear terms for each predictor.

The model created is normally affected by the response errors. It is commonly assumed that the response errors follow a normal distribution and that extreme values are rare. However, extreme values called outliers do occur and the linear models are very sensitive to these values. Outliers have a large influence on the fit, because squaring the ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required