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Authors: Jongseong Kim and Hoo-Gon Choi

Affiliation: Sungkyunkwan University, Korea, Republic of

ISBN: 978-989-8565-18-1

Keyword(s): Diagnosis Model, Genetic Programming, Absorbing Evolution, Accuracy and Recall Rate, Computing Time.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Datamining ; Enterprise Information Systems ; Health Information Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: An accurate diagnosis model is required to diagnose the medical subjects. The subjects should be diagnosed with high accuracy and recall rate by the model. The laboratory test data are collected from 953 latent subjects having type 2 diabetes mellitus. The results are classified into patient group and normal group by using support vector machine kernels optimized through genetic programming. Genetic programming is applied for the input data twice with absorbing evolution, which is a new approach. The result shows that new approach creates a kernel with 80% accuracy, 0.794 recall rate and 28% reduction of computing time comparing to other typical methods. Also, the suggested kernel can be easily utilized by users having no and little experience on large data.

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Paper citation in several formats:
Kim, J. and Choi, H. (2012). Kernel Generations for a Diagnosis Model with GP.In Proceedings of the International Conference on Data Technologies and Applications - Volume 1: DATA, ISBN 978-989-8565-18-1, pages 57-62. DOI: 10.5220/0004028500570062

@conference{data12,
author={Jongseong Kim. and Hoo{-}Gon Choi.},
title={Kernel Generations for a Diagnosis Model with GP},
booktitle={Proceedings of the International Conference on Data Technologies and Applications - Volume 1: DATA,},
year={2012},
pages={57-62},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004028500570062},
isbn={978-989-8565-18-1},
}

TY - CONF

JO - Proceedings of the International Conference on Data Technologies and Applications - Volume 1: DATA,
TI - Kernel Generations for a Diagnosis Model with GP
SN - 978-989-8565-18-1
AU - Kim, J.
AU - Choi, H.
PY - 2012
SP - 57
EP - 62
DO - 10.5220/0004028500570062

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