Partial least squares classification for high dimensional data using the PCOUT algorithm
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سال
: 2013شناسه الکترونیک: 10.1007/s00180-012-0328-y
کلیدواژه(گان): Classification,Outlier,Partial least squares,PCOUT,Robustness
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Partial least squares classification for high dimensional data using the PCOUT algorithm
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| contributor author | Turkmen, A. - Billor, N. | |
| date accessioned | 2020-03-11T15:33:24Z | |
| date available | 2020-03-11T15:33:24Z | |
| date issued | 2013 | |
| identifier issn | 0943-4062 | |
| identifier other | 10.1007-s00180-012-0328-y.pdf | |
| identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/578045?locale-attribute=fa | |
| format | general | |
| language | English | |
| publisher | Springer-Verlag | |
| title | Partial least squares classification for high dimensional data using the PCOUT algorithm | |
| type | Journal Paper | |
| contenttype | Metadata Only | |
| identifier padid | 4431197 | |
| subject keywords | Classification | |
| subject keywords | Outlier | |
| subject keywords | Partial least squares | |
| subject keywords | PCOUT | |
| subject keywords | Robustness | |
| identifier doi | 10.1007/s00180-012-0328-y | |
| journal title | Computational Statistics | |
| journal volume | 28 | |
| journal issue | 2 | |
| filesize | 304930 | |
| citations | 0 |