Our data science expert continues his exploration of neural network programming, explaining how regularization addresses the problem of model overfitting, caused by network overtraining. Neural ...

Data structures in modern applications frequently combine the necessity of flexible regression techniques handling, for example, non-linear and spatial effects with high dimensional covariate vectors.

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 ...