"In recent years, researchers have made considerable progress on the of inductive learning tasks, but for theoretical results to have impact on practice, they must deal with the average case. In this paper we present an average-case analysis of a simple algorithm that induces one-level decision trees for concepts defined by a single relevant attribute. Given knowledge about the number of training instances, the number of irrelevant attributes, the amount of class and attribute noise, and the class and attribute distributions, we derive the expected classification accuracy over the entire instance space. We then examine the predictions of this analysis for different settings of these domain parameters, comparing them to experimental results to check our reasoning."
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Pat Langley
Pat Langley (born May 2, 1953) is an American cognitive scientist and AI researcher, Honorary Professor of Computer Science at the University of Auckland, and Director of the Institute for the Study of Learning and Expertise. He coined the term decision stump and was founding editor of journals Machine Learning and Advances in Cognitive Systems.
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