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Accuracy Vs. Comprehensibility in Data Mining Models

Category: Data Management

Tags: data mining, data

Overview This paper addresses the important issue of the tradeoff between accuracy and comprehensibility in data mining. The paper presents results which show that it is, to some extent, possible to bridge this gap. A method for rule extraction from opaque models (Genetic Rule EXtraction - G-REX) is used to show the effects on accuracy when forcing the creation of comprehensible representations. In addition the technique of combining different classifiers to an ensemble is demonstrated on some well-known data sets. The results show that ensembles generally have very high accuracy, thus making them a good first choice when performing predictive data mining.

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Publisher
University of Sk?vde
File Format
PDF
Date Published
Sep 19, 2008
Format
White Papers
Topics
Knowledge and Data Management, Data Mining - Analysis

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