ML-Ensemble is a high performance library for ensemble learning. It emphasizes memory efficient paralelization and user friendliness. It deploys a Scikit-learn-style API together with a modular ensemble network API to provide users with simple, transparent tools for building parallelized multi-layer ensembles. For more details, see the project's homepage.

Ensemble learning

Explaining how and what ensembles learn

You may have wondered why there are so many different algorithms for machine learning - after all, would it not be sufficient with one algorithm? A famous result is the no free lunch theorem, which tells us that no one algorithm will be optimal for every problem. [Read More]
Tags: Machine Learning