Vif Linear Regression Python. So what to do. Apply the model for predictions.
1 1 R2. Y datax_var_namesi x datax_var_namesdropx_var_namesi r_squared smOLSyxfitrsquared vif round11-r_squared2 vif_dfloci x_var_namesi vif. So which one 5 or 10.
We assume the relationship to be linear and our dependent variable must be continuous in nature.
Linear Regression Introduction to Linear Regression Linear Regression is a supervised statistical technique where we try to estimate the dependent variable with a given set of independent variables. Steps for Implementing VIF Step 1. We assume the relationship to be linear and our dependent variable must be continuous in nature. Colinearity is the state where two variables are highly correlated and contain similiar information about the variance within a given dataset.