Generalized Linear Models

Here general refers to the dependence on potentially more than one explanatory variable, v.s. the simple linear model :
Some of the Generalized liner models are:

1-Ordinary Least Squares :Linear Regression fits a linear model with coefficients w = (w_1, ..., w_p) to minimize the residual sum of squares between the observed responses in the data set, and the responses predicted by the linear approximation. Mathematically:

\underset{w}{min\,} {|| X w - y||_2}^2

 

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