The ridge regression, as a biased estimation method for analyzing collinear data, can be considered as the fundamental basis of all machine learning algorithms. This paper presents a novel deep ridge ...

The complexity of tuning and intensive computation required by deep models often leads to overfitting when applied to small data sets. When dealing with small data sets, traditional machine learning ...

Added in version 7.2.2 LOGEST is based on the same calculations as LINEST, including how it handles collinearity for multiple regression analysis. However, the function returns statistics to a curve ...

Bayesian probability of agreement for comparing survival or reliability functions with parametric lifetime regression models Citation: Stevens, N. T. , Lu, L. , Anderson-Cook, C. M. , & Rigdon, S. .

We study a graph-constrained regularization procedure and its theoretical properties for regression analysis to take into account the neighborhood information of the variables measured on a graph.

We investigate a longitudinal data model with non-parametric regression functions that may vary across the observed individuals. In a variety of applications, it is natural to impose a group structure ...