Decision Tree Induction Systems: A Bayesian Analysis

📝 Original Info

• Title: Decision Tree Induction Systems: A Bayesian Analysis
• ArXiv ID: 1304.2732
• Date: 2013-04-11
• Authors: ** J. R. Quinlan, J. G. (et al.) **

📝 Abstract

Decision tree induction systems are being used for knowledge acquisition in noisy domains. This paper develops a subjective Bayesian interpretation of the task tackled by these systems and the heuristic methods they use. It is argued that decision tree systems implicitly incorporate a prior belief that the simpler (in terms of decision tree complexity) of two hypotheses be preferred, all else being equal, and that they perform a greedy search of the space of decision rules to find one in which there is strong posterior belief. A number of improvements to these systems are then suggested.

💡 Deep Analysis

Deep Dive into Decision Tree Induction Systems: A Bayesian Analysis.

Decision tree induction systems are being used for knowledge acquisition in noisy domains. This paper develops a subjective Bayesian interpretation of the task tackled by these systems and the heuristic methods they use. It is argued that decision tree systems implicitly incorporate a prior belief that the simpler (in terms of decision tree complexity) of two hypotheses be preferred, all else being equal, and that they perform a greedy search of the space of decision rules to find one in which there is strong posterior belief. A number of improvements to these systems are then suggested.

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