This paper proposes a regularized regression procedure for finding a predictive relation between one variable and a field of other variables. The procedure estimates a linear prediction model under ...

When you’re building a machine learning model you’re faced with the bias-variance tradeoff, where you have to find the balance between having a model that: Is very expressive and captures the real ...

Many regression analyses involve explanatory variables that are measured with error, and failing to account for this error is well known to lead to biased point and ...

The adjusted r-squared is helpful for multiple regression and corrects for erroneous regression, giving you a more accurate correlation coefficient. If you look at the multiple regression we did, ...