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Authors: Senko Oleg 1 and Kuznetsova Anna 2

Affiliations: 1 Dorodnicyn Computer Center of Russian Academy of Sciences, Russian Federation ; 2 Emanuel Institute of Biochemical Physics of Russian Academy of Sciences, Russian Federation

Keyword(s): Empirical regularities, Optimal partitioning, Permutation tests.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; BioInformatics & Pattern Discovery ; Business Analytics ; Computational Intelligence ; Data Analytics ; Data Engineering ; Evolutionary Computing ; Foundations of Knowledge Discovery in Databases ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Mining High-Dimensional Data ; Soft Computing ; Symbolic Systems

Abstract: The goal of discussed Optimal valid partitioning (OVP) method is discovering of regularities describing effect of explanatory variables on outcome value. OVP method is based on searching partitions of explanatory variables space with best possible separation of objects with different levels of outcome variable. Optimal partitions are searched inside several previously defined families by empirical (training) datasets. Random permutation tests are used for assessment of statistical validity and optimization of used models complexity. Additional mathematical tools that are aimed at improving performance of OVP approach are discussed. They include methods for evaluating structure of found regularities systems and estimating importance of explanatory variables. Paper also represents variant of OVP technique that allows to compare effects of explanatory variables on outcome in different groups of objects.

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Paper citation in several formats:
Oleg, S. and Anna, K. (2011). METHODS FOR DISCOVERING AND ANALYSIS OF REGULARITIES SYSTEMS - Approach based on Optimal Partitioning of Explanatory Variables Space. In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2011) - KDIR; ISBN 978-989-8425-79-9; ISSN 2184-3228, SciTePress, pages 415-418. DOI: 10.5220/0003639104230426

@conference{kdir11,
author={Senko Oleg. and Kuznetsova Anna.},
title={METHODS FOR DISCOVERING AND ANALYSIS OF REGULARITIES SYSTEMS - Approach based on Optimal Partitioning of Explanatory Variables Space},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2011) - KDIR},
year={2011},
pages={415-418},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003639104230426},
isbn={978-989-8425-79-9},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2011) - KDIR
TI - METHODS FOR DISCOVERING AND ANALYSIS OF REGULARITIES SYSTEMS - Approach based on Optimal Partitioning of Explanatory Variables Space
SN - 978-989-8425-79-9
IS - 2184-3228
AU - Oleg, S.
AU - Anna, K.
PY - 2011
SP - 415
EP - 418
DO - 10.5220/0003639104230426
PB - SciTePress

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