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» Efficient Distributed Genetic Algorithm for Rule Extraction
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GECCO
2000
Springer
112views Optimization» more  GECCO 2000»
13 years 10 months ago
Linguistic Rule Extraction by Genetics-Based Machine Learning
This paper shows how linguistic classification knowledge can be extracted from numerical data for pattern classification problems with many continuous attributes by genetic algori...
Hisao Ishibuchi, Tomoharu Nakashima
FUZZIEEE
2007
IEEE
14 years 18 days ago
A Genetic-Fuzzy Mining Approach for Items with Multiple Minimum Supports
—In the past, we proposed a genetic-fuzzy data-mining algorithm for extracting both association rules and membership functions from quantitative transactions under a single minim...
Chun-Hao Chen, Tzung-Pei Hong, Vincent S. Tseng, C...
IEEECGIV
2005
IEEE
13 years 12 months ago
Automatic Feature Extraction and Stereo Image Processing with Genetic Algorithms for LiDAR Data
Aerial photos with LiDAR data were processed with genetic algorithms for not only the feature extraction but also orthographical image. DSM provided by LiDAR reduced the amount of...
Teng-To Yu, Ming Yang, Chao-Shi Chen
CEC
2009
IEEE
13 years 11 months ago
Distributed genetic algorithm using automated adaptive migration
—We present a new distributed genetic algorithm that can be used to extract useful information from distributed, large data over the network. The main idea of the proposed algori...
Hyunjung Lee, Byonghwa Oh, Jihoon Yang, Seonho Kim
FLAIRS
2008
13 years 8 months ago
Using Genetic Programming to Increase Rule Quality
Rule extraction is a technique aimed at transforming highly accurate opaque models like neural networks into comprehensible models without losing accuracy. G-REX is a rule extract...
Rikard König, Ulf Johansson, Lars Niklasson