Self-adjusting harmony search-based feature selection
| LEADER | caa a22 4500 | ||
|---|---|---|---|
| 001 | 605468540 | ||
| 003 | CHVBK | ||
| 005 | 20210128100317.0 | ||
| 007 | cr unu---uuuuu | ||
| 008 | 210128e20150601xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s00500-014-1307-8 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s00500-014-1307-8 | ||
| 245 | 0 | 0 | |a Self-adjusting harmony search-based feature selection |h [Elektronische Daten] |c [Ling Zheng, Ren Diao, Qiang Shen] |
| 520 | 3 | |a Many strategies have been exploited for the task of feature selection, in an effort to identify more compact and better quality feature subsets. The development of nature-inspired stochastic search techniques allows multiple good quality feature subsets to be discovered without resorting to exhaustive search. In particular, harmony search is a recently developed technique mimicking musicians' experience, which has been effectively utilised to cope with feature selection problems. In this paper, a self-adjusting approach is proposed for feature selection with an aim to further enhance the performance of the existing harmony search-based method. This novel approach includes three dynamic strategies: restricted feature domain, harmony memory consolidation, and pitch adjustment. Systematic experimental evaluations using high dimensional, real-valued benchmark data sets are conducted in order to verify the efficacy of the proposed work. | |
| 540 | |a Springer-Verlag Berlin Heidelberg, 2014 | ||
| 690 | 7 | |a Feature selection |2 nationallicence | |
| 690 | 7 | |a Harmony search |2 nationallicence | |
| 690 | 7 | |a Harmony memory consolidation |2 nationallicence | |
| 690 | 7 | |a Pitch adjustment strategy |2 nationallicence | |
| 700 | 1 | |a Zheng |D Ling |u Department of Computer Science, Institute of Mathematics, Physics and Computer Science, Aberystwyth University, Aberystwyth, UK |4 aut | |
| 700 | 1 | |a Diao |D Ren |u Department of Computer Science, Institute of Mathematics, Physics and Computer Science, Aberystwyth University, Aberystwyth, UK |4 aut | |
| 700 | 1 | |a Shen |D Qiang |u Department of Computer Science, Institute of Mathematics, Physics and Computer Science, Aberystwyth University, Aberystwyth, UK |4 aut | |
| 773 | 0 | |t Soft Computing |d Springer Berlin Heidelberg |g 19/6(2015-06-01), 1567-1579 |x 1432-7643 |q 19:6<1567 |1 2015 |2 19 |o 500 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s00500-014-1307-8 |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/s00500-014-1307-8 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Zheng |D Ling |u Department of Computer Science, Institute of Mathematics, Physics and Computer Science, Aberystwyth University, Aberystwyth, UK |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Diao |D Ren |u Department of Computer Science, Institute of Mathematics, Physics and Computer Science, Aberystwyth University, Aberystwyth, UK |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Shen |D Qiang |u Department of Computer Science, Institute of Mathematics, Physics and Computer Science, Aberystwyth University, Aberystwyth, UK |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Soft Computing |d Springer Berlin Heidelberg |g 19/6(2015-06-01), 1567-1579 |x 1432-7643 |q 19:6<1567 |1 2015 |2 19 |o 500 | ||