An incremental piecewise linear classifier based on polyhedral conic separation
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| 008 | 210128e20151001xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s10994-014-5449-9 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s10994-014-5449-9 | ||
| 245 | 0 | 3 | |a An incremental piecewise linear classifier based on polyhedral conic separation |h [Elektronische Daten] |c [Gurkan Ozturk, Adil Bagirov, Refail Kasimbeyli] |
| 520 | 3 | |a In this paper, a piecewise linear classifier based on polyhedral conic separation is developed. This classifier builds nonlinear boundaries between classes using polyhedral conic functions. Since the number of polyhedral conic functions separating classes is not known a priori, an incremental approach is proposed to build separating functions. These functions are found by minimizing an error function which is nonsmooth and nonconvex. A special procedure is proposed to generate starting points to minimize the error function and this procedure is based on the incremental approach. The discrete gradient method, which is a derivative-free method for nonsmooth optimization, is applied to minimize the error function starting from those points. The proposed classifier is applied to solve classification problems on 12 publicly available data sets and compared with some mainstream and piecewise linear classifiers. | |
| 540 | |a The Author(s), 2014 | ||
| 690 | 7 | |a Classification |2 nationallicence | |
| 690 | 7 | |a Polyhedral conic separation |2 nationallicence | |
| 690 | 7 | |a Nonsmooth nonconvex optimization |2 nationallicence | |
| 690 | 7 | |a Discrete gradient method |2 nationallicence | |
| 700 | 1 | |a Ozturk |D Gurkan |u Department of Industrial Engineering, Faculty of Engineering, Anadolu University, 26555, Eskisehir, Turkey |4 aut | |
| 700 | 1 | |a Bagirov |D Adil |u School of Science, Information Technology and Engineering, Federation University Australia, 3353, Ballarat, VIC, Australia |4 aut | |
| 700 | 1 | |a Kasimbeyli |D Refail |u Department of Industrial Engineering, Faculty of Engineering, Anadolu University, 26555, Eskisehir, Turkey |4 aut | |
| 773 | 0 | |t Machine Learning |d Springer US; http://www.springer-ny.com |g 101/1-3(2015-10-01), 397-413 |x 0885-6125 |q 101:1-3<397 |1 2015 |2 101 |o 10994 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s10994-014-5449-9 |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/s10994-014-5449-9 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Ozturk |D Gurkan |u Department of Industrial Engineering, Faculty of Engineering, Anadolu University, 26555, Eskisehir, Turkey |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Bagirov |D Adil |u School of Science, Information Technology and Engineering, Federation University Australia, 3353, Ballarat, VIC, Australia |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Kasimbeyli |D Refail |u Department of Industrial Engineering, Faculty of Engineering, Anadolu University, 26555, Eskisehir, Turkey |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Machine Learning |d Springer US; http://www.springer-ny.com |g 101/1-3(2015-10-01), 397-413 |x 0885-6125 |q 101:1-3<397 |1 2015 |2 101 |o 10994 | ||