1. A system for training an entity model, comprising: at least one computer device including: a feature correlation system that groups features from an inputted feature data sample into subsets based on which features have the most characteristics in common, the grouping being determined by the at least one computer device; a plurality of classifiers that determine if each feature classifies into an associated one of a plurality of feature models that make up the entity model; and a boosting system that boosts features from a subset for a next round of training if any of the features classify and at least one correlated feature from the subset does not classify, wherein for each of the features that classify, a plurality of clones of the feature are generated for multiple future uses.