Variable Selection and Decision Trees: The DiVaS and ALoVaS Methods
In this thesis we propose a novel modification to Bayesian decision tree methods. We provide a historical survey of the statistics and computer science research in decision trees. Our approach facilitates covariate selection explicitly in the model, something not present in previous research. We def...
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Format: | Others |
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Virginia Tech
2016
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Online Access: | http://hdl.handle.net/10919/70878 |