NEATER: filtering of over-sampled data using non-cooperative game theory
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| 024 | 7 | 0 | |a 10.1007/s00500-014-1484-5 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s00500-014-1484-5 | ||
| 245 | 0 | 0 | |a NEATER: filtering of over-sampled data using non-cooperative game theory |h [Elektronische Daten] |c [B. Almogahed, I. Kakadiaris] |
| 520 | 3 | |a In this paper, we present a method for the filteriNg of ovEr-sampled dAta using non-cooperaTive gamE theoRy (NEATER) to address the imbalanced data problem. Specifically, the problem is formulated as a non-cooperative game where all the data are players and the goal is to uniformly and consistently label all of the synthetic data created by any over-sampling technique. The proposed algorithm does not require any prior assumptions and selects representative synthetic instances while generating a very small number of noisy data. We present extensive experimental results over a large collection of datasets using three different classifiers to demonstrate the advantages of our method. | |
| 540 | |a Springer-Verlag Berlin Heidelberg, 2014 | ||
| 690 | 7 | |a Imbalanced data |2 nationallicence | |
| 690 | 7 | |a Classification |2 nationallicence | |
| 690 | 7 | |a Sampling |2 nationallicence | |
| 700 | 1 | |a Almogahed |D B. |u Computational Biomedicine Lab, Department of Computer Science, University of Houston, Houston, USA |4 aut | |
| 700 | 1 | |a Kakadiaris |D I. |u Computational Biomedicine Lab, Department of Computer Science, University of Houston, Houston, USA |4 aut | |
| 773 | 0 | |t Soft Computing |d Springer Berlin Heidelberg |g 19/11(2015-11-01), 3301-3322 |x 1432-7643 |q 19:11<3301 |1 2015 |2 19 |o 500 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s00500-014-1484-5 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s00500-014-1484-5 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Almogahed |D B. |u Computational Biomedicine Lab, Department of Computer Science, University of Houston, Houston, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Kakadiaris |D I. |u Computational Biomedicine Lab, Department of Computer Science, University of Houston, Houston, USA |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Soft Computing |d Springer Berlin Heidelberg |g 19/11(2015-11-01), 3301-3322 |x 1432-7643 |q 19:11<3301 |1 2015 |2 19 |o 500 | ||