Oct. 3, 2023, 12:52 a.m. | Synced

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In a new paper MAPTree: Beating "Optimal" Decision Trees with Bayesian Decision Trees, a Stanford University research team introduces MAPTree, an algorithm that confidently uncovers the maximum a posteriori tree within Bayesian Classification and Regression Trees (BCART) posterior, achieving strong performance with significantly leaner and faster trees.


The post Standford U’s MAPTree: Redefining Decision Trees – Precision, Speed, and Efficiency Unleashed first appeared on Synced.

ai algorithm artificial intelligence bayesian bayesian deep learning classification decision decision-tree decision trees deep-neural-networks efficiency faster machine learning machine learning & data science ml paper performance posterior precision regression research research team speed stanford stanford university team technology tree trees university university research

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