Titlebook: Intelligent Data Engineering and Automated Learning - IDEAL 2002; Third International Hujun Yin,Nigel Allinson,Simon Hubbard Conference pr

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Co-evolutionary Data Mining to Discover Rules for Fuzzy Resource Managements being explored that involves embedding the resource manager in an electronic game environment. The game allows a human expert to play against the resource manager in a simulated battlespace with each of the defending platforms being exclusively directed by the fuzzy resource manager and the attack

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Discovering Temporal Rules from Temporally Ordered Dataaracterize the behavior of a single system. Data are gathered from variables of the system, and used to discover relations among the variables. In general, such rules could be causal or acausal. We formally characterize the problem and introduce RFCT, a hybrid tool based on the C4.5 classification s

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T3: A Classification Algorithm for Data Miningthe tree reasonably small. T3 is an improvement over T2 in that it builds larger trees and adopts a less greedy approach. T3 gave better results than both T2 and C4.5 when run against publicly available data sets: T3 decreased classification error on average by 47% and generalisation error by 29%, c

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