A Python library for dynamic classifier and ensemble selection

This work was aimed at finding methods to identify the most distant proteins and most diverse subsets of proteins from large protein databases in a scalable and efficient way using a dataset of protein embeddings from SwissProt, data mining techniques and metaheuristics.

Small collection of Diversity Measures for Ensemble Learning Predictions

Diversity / (dis)proportionality measures, election quotas, and apportionment methods in pure Python.

Experiment on the pruning of pool of classifiers