Robust classifier using distance-based representation with square weights
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| 001 | 605470537 | ||
| 003 | CHVBK | ||
| 005 | 20210128100328.0 | ||
| 007 | cr unu---uuuuu | ||
| 008 | 210128e20150201xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s00500-014-1272-2 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s00500-014-1272-2 | ||
| 245 | 0 | 0 | |a Robust classifier using distance-based representation with square weights |h [Elektronische Daten] |c [Jiangshu Wei, Jian Lv, Zhang Yi] |
| 520 | 3 | |a This paper presents a new multi-class classification method that is different from sparse representation classifier (SRC) method. SRC is a classical method which has been widely used for face recognition and digit identification. However, SRC method only looks for the sparsest solution using $$l_1$$ l 1 norm minimization with high computation complexity. The sparsest representation cannot show the space distribution feature of samples. Moreover, the sparsest representation does not mean obtaining the highest recognition rate for data classification. This paper proposes a distance-based representation method for classification. The distance between samples is used to measure the similarity. It is crucial that square weights $$x_i^2$$ x i 2 are used as the weight of distance instead of $$x_i$$ x i . Furthermore, a closed form solution is obtained so that the computation complexity is lower than that of SRC. The extensive experiments show that the proposed method achieves very competitive classification results. | |
| 540 | |a Springer-Verlag Berlin Heidelberg, 2014 | ||
| 700 | 1 | |a Wei |D Jiangshu |u Machine Intelligence Laboratory, College of Computer Science, Sichuan University, 610065, Chengdu, People's Republic of China |4 aut | |
| 700 | 1 | |a Lv |D Jian |u Machine Intelligence Laboratory, College of Computer Science, Sichuan University, 610065, Chengdu, People's Republic of China |4 aut | |
| 700 | 1 | |a Yi |D Zhang |u Machine Intelligence Laboratory, College of Computer Science, Sichuan University, 610065, Chengdu, People's Republic of China |4 aut | |
| 773 | 0 | |t Soft Computing |d Springer Berlin Heidelberg |g 19/2(2015-02-01), 507-515 |x 1432-7643 |q 19:2<507 |1 2015 |2 19 |o 500 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s00500-014-1272-2 |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/s00500-014-1272-2 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Wei |D Jiangshu |u Machine Intelligence Laboratory, College of Computer Science, Sichuan University, 610065, Chengdu, People's Republic of China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Lv |D Jian |u Machine Intelligence Laboratory, College of Computer Science, Sichuan University, 610065, Chengdu, People's Republic of China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Yi |D Zhang |u Machine Intelligence Laboratory, College of Computer Science, Sichuan University, 610065, Chengdu, People's Republic of China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Soft Computing |d Springer Berlin Heidelberg |g 19/2(2015-02-01), 507-515 |x 1432-7643 |q 19:2<507 |1 2015 |2 19 |o 500 | ||