Support vector machine in chemistry
In recent years, the support vector machine (SVM), a new data processing method, has been applied to many fields of chemistry and chemical technology. Compared with some other data processing methods, SVM is especially suitable for solving problems of small sample size, with superior prediction perf...
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| Format: | Elektronisch E-Book |
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| Sprache: | English |
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World Scientific Pub. Co.
c2004
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| Online-Zugang: | DE-92 URL des Erstveroeffentlichers |
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| 520 | |a In recent years, the support vector machine (SVM), a new data processing method, has been applied to many fields of chemistry and chemical technology. Compared with some other data processing methods, SVM is especially suitable for solving problems of small sample size, with superior prediction performance. SVM is fast becoming a powerful tool of chemometrics. This book provides a systematic approach to the principles and algorithms of SVM, and demonstrates the application examples of SVM in QSAR/QSPR work, materials and experimental design, phase diagram prediction, modeling for the optimal control of chemical industry, and other branches in chemistry and chemical technology | ||
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| id | DE-604.BV044635635 |
| illustrated | Illustrated |
| indexdate | 2024-12-24T06:13:56Z |
| institution | BVB |
| isbn | 9789812794710 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030033607 |
| oclc_num | 1012670469 |
| open_access_boolean | |
| owner | DE-92 |
| owner_facet | DE-92 |
| physical | x, 331 p. ill |
| psigel | ZDB-124-WOP ZDB-124-WOP FHN_PDA_WOP |
| publishDate | 2004 |
| publishDateSearch | 2004 |
| publishDateSort | 2004 |
| publisher | World Scientific Pub. Co. |
| record_format | marc |
| spelling | Support vector machine in chemistry Nianyi Chen ... [et al.] Singapore World Scientific Pub. Co. c2004 x, 331 p. ill txt rdacontent c rdamedia cr rdacarrier In recent years, the support vector machine (SVM), a new data processing method, has been applied to many fields of chemistry and chemical technology. Compared with some other data processing methods, SVM is especially suitable for solving problems of small sample size, with superior prediction performance. SVM is fast becoming a powerful tool of chemometrics. This book provides a systematic approach to the principles and algorithms of SVM, and demonstrates the application examples of SVM in QSAR/QSPR work, materials and experimental design, phase diagram prediction, modeling for the optimal control of chemical industry, and other branches in chemistry and chemical technology Machine learning Algorithms Kernel functions Chen, Nianyi Sonstige oth Erscheint auch als Druck-Ausgabe 9789812389220 Erscheint auch als Druck-Ausgabe 9812389229 http://www.worldscientific.com/worldscibooks/10.1142/5589#t=toc Verlag URL des Erstveroeffentlichers Volltext |
| spellingShingle | Support vector machine in chemistry Machine learning Algorithms Kernel functions |
| title | Support vector machine in chemistry |
| title_auth | Support vector machine in chemistry |
| title_exact_search | Support vector machine in chemistry |
| title_full | Support vector machine in chemistry Nianyi Chen ... [et al.] |
| title_fullStr | Support vector machine in chemistry Nianyi Chen ... [et al.] |
| title_full_unstemmed | Support vector machine in chemistry Nianyi Chen ... [et al.] |
| title_short | Support vector machine in chemistry |
| title_sort | support vector machine in chemistry |
| topic | Machine learning Algorithms Kernel functions |
| topic_facet | Machine learning Algorithms Kernel functions |
| url | http://www.worldscientific.com/worldscibooks/10.1142/5589#t=toc |
| work_keys_str_mv | AT chennianyi supportvectormachineinchemistry |