Multivariate Adaptive Regression Splines (MARS) is a supervised learning model in machine learning, not obtained by an ensemble method. Ensemble methods are gathered from samples comprising hundreds or thousands of learners that serve the common purpose improving stability and accuracy algorithms. This study presented REMARS (Random MARS), new MARS selection approach using Random Forest (RF) al...

using monthly test day records the genetic parameters of iranian holstein cattle in first lactation were studied. data of 277400 test-day milk records from 65320 cows and 2210 sires were analyzed by an animal random regression model using restricted maximum likelihood methodology. the model included herd-test-date, interaction between year-season of calving, days in milk (linear and quadratic) ...

in this study a total of 171,360 monthly test day milk records obtained from first lactation of iranian holstein cattle (three times a day milking) distributed in 96 herds and calved from 1999 to 2008 were used to estimate genetic parameters and to predict breeding values of the animals. the data was analyzed using random regression test day model. the results showed that average of heritabilit...

This paper examines the validity of some stylized statements that can be found in the actuarial literature about random effects models. Specifically, the actual meaning of the estimated parameters and the nature of the residual heterogeneity are discussed. A numerical illustration performed on a Belgian motor third party liability portfolio supports this discussion.