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Project: Generative Random Forests: The Next Level

Description

The work on generative random forests has started, but there is a long way to make them practical. This project aims at studying the drawbacks of such models and improving them with better ensemble ideas, gradient boosting, and/or other techniques already employed with decision trees and random forests but still not available for the generative counterpart. We may also explore means to learn the trees in a generative manner instead of discriminatively (as usually done for building classifiers). This could be useful, for instance, for creating a stronger generative model able to perform different queries and for multi-dimensional classification.

References:

https://arxiv.org/abs/2308.03648

https://arxiv.org/abs/2006.14937

Details

Supervisor

Cassio de Campos

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