What impact cause feature scaling on the model performance?
While working with data preprocessing before modelling few questions rose in my head. Is it possible that by applying scaling, some of the significant features will lose their weight, and thus have lower impact to explaining the variance of the response variable? If yes, if some important features would be identified by expert knowledge, is it OK to scale other features but those? Or I need to scale only the significant features?