Abstract: Random Forest is a well-known type of ensemble learning, which combines a number of decision trees to improve the prediction ability and reduce the risk of overfitting. This paper aims at ...
Abstract: Some problems arise in analyzing massive complex data consisting of multivariate response variables and a large number of multicollinear predictor variables, especially when the sample sizes ...