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Authors: Bernardete M. Ribeiro 1 ; Andrew Sung 2 ; Divya Suryakumar 3 and Ram Basnet 4

Affiliations: 1 University of Coimbra, Portugal ; 2 University of Southern Mississippi, United States ; 3 Apple and Inc., United States ; 4 Colorado Mesa University, United States

Keyword(s): Data Mining, Knowledge Discovery, Critical Feature Dimension, Critical Sampling Random Selection.

Related Ontology Subjects/Areas/Topics: Feature Selection and Extraction ; Model Selection ; Pattern Recognition ; Theory and Methods

Abstract: Efficacious data mining methods are critical for knowledge discovery in various applications in the era of big data. Two issues of immediate concern in big data analytic tasks are how to select a critical subset of features and how to select a critical subset of data points for sampling. This position paper presents ongoing research by the authors that suggests: 1. the critical feature dimension problem is theoretically intractable, but simple heuristic methods may well be sufficient for practical purposes; 2. there are big data analytic problems where the success of data mining depends more on the critical feature dimension than the specific features selected, thus a random selection of the features based on the dataset’s critical feature dimension will prove sufficient; and 3. The problem of critical sampling has the same intractable complexity as critical feature dimension, but again simple heuristic methods may well be practicable in most applications.

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Paper citation in several formats:
Ribeiro, B.; Sung, A.; Suryakumar, D. and Basnet, R. (2015). The Critical Feature Dimension and Critical Sampling Problems. In Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-076-5; ISSN 2184-4313, pages 360-366. DOI: 10.5220/0005282403600366

@conference{icpram15,
author={Bernardete M. Ribeiro. and Andrew Sung. and Divya Suryakumar. and Ram Basnet.},
title={The Critical Feature Dimension and Critical Sampling Problems},
booktitle={Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2015},
pages={360-366},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005282403600366},
isbn={978-989-758-076-5},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - The Critical Feature Dimension and Critical Sampling Problems
SN - 978-989-758-076-5
IS - 2184-4313
AU - Ribeiro, B.
AU - Sung, A.
AU - Suryakumar, D.
AU - Basnet, R.
PY - 2015
SP - 360
EP - 366
DO - 10.5220/0005282403600366

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