We also develop Machine Learning, Data Mining and more in general Data Analytics methods that may have a wide application scope, also outside Computational Biology and Bioinformatics:
- Hyper-ensemble methods for unbalanced classification problems with big data
- Multiclass, multi-label and multi-path hierarchical ensemble methods
- Ensemble methods based on the decomposition of the error into bias and variance
- Supervised ensemble methods based on randomized projections
- Ensemble methods with error correction codes for multiclass classification.
- Ensemble clustering methods
- Semi-supervised graph learning