It is possible to post-process decision tree prediction rules to remove unnecessary duplication of predictor variables, but the demo program, and most machine learning library implementations, do not ...

Prognostic models for 12-months mortality were built using Cox regression model, single decision tree (DT) and random survival forest (RSF). Models performance was compared based on externally ...

In machine learning, typically non-linear regression techniques are used. Examples of nonlinear regression algorithms include gradient descent, Gauss-Newton, and the Levenberg-Marquardt methods.

Recent scientific article explores the use of machine learning techniques to identify the key risk factors associated with ...

Our news correspondents obtained a quote from the research from University of Minnesota: “To better predict the demand for health insurance, three regression models in machine learning - random ...

It is possible to post-process decision tree prediction rules to remove unnecessary duplication of predictor variables, but the demo program, and most machine learning library implementations, do not ...