Data Analytics

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