What is ELF

ELF stands for "Ensemble Learning Framework".

This piece of software, written in C++, is constructed being a stand-alone supervised machine learning framework. ELF is able to solve regression as well as classification problems. Our goal is doing this as accurate and as fast as possible. Recently, ensemble learning turns out to be very popular. The ELF supports ensembling in some ways.

The optimization target can be the RMSE, MAE, AUC or the classification error. The ELF supports multi-class classification problems and multi-domain classification. Multi-domain means that we have more than one label per example. The ELF has well implemented base learners. The ensemble functionality of the framework is realized with stacking, cascade learning and residual training. Stacking is a simple linear combination. ELF has the opportunity of cascade learning, which is an extention of the features with predictions from other models. Parameter selection can be done with cross-validation or bagging. Parameter selection means searching for good metaparameters in order to control overfitting of each individual model.