Regression model evaluation parameters Introduction

Taking into account to evaluate the effect of a regression model, including the fitting of the general effect by correcting R2, the R2 has a unique method of calculation, the correlation coefficient is not, of course, is not the correlation coefficient R2.

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If you look at the corresponding variables from the regression model species explanation variable rate, typically using the standardized coefficients, the normalized regression coefficient value is sometimes not automatically calculated R languages, may have some of the functions by himself or other packages of manual calculation, but according to other information, the regression coefficient is normalized raw data (including the independent and dependent variable) is calculated after normalization, removal dimensionless. Thus it can judge the impact of a change of circumstances independent variable on the dependent variable.

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