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A Framework for Multi-View Classification of Features
In this research, an innovative framework for multi-view ensemble classification, inspired by the problem of object recognition in the multiple views theory of humans, is proposed.
Crossbreeding in Random Forest
Ensemble learning methods are designed to benefit from multiple learning algorithms for better predictive performance.
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