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| Format: | Artículo científico |
| Language: | pt |
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Universidade Estadual Paulista Júlio de Mesquita Filho
2011
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| Online Access: | https://www.redalyc.org/articulo.oa?id=42938349004 |
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Table of Contents:
- SELEÇÃO DE VARIÁVEIS PARA CATEGORIZAÇÃO DE AMOSTRAS QUÍMICAS M. J. Anzanello Química PLS regression chemical samples Variable selection This paper presents a method to select the best variables to categorize chemical samples into two classes, say conforming or non-conforming. For that matter, PLS regression is combined with a data mining tool, the k-Nearest Neighbor classi¿cation technique, through an iterative variable selection process. The recommended subset of variables is chosen based on several criteria: sensitivity, speci¿city and percent of retained variables. When applied to two datasets related to wine analysis and one associated to QSAR, the proposed method signi¿cantly reduced the number of variables required for classi¿cation, while yielding superior categorization performance when compared to using all original variables. 2011 artículo científico 0100-4670 https://www.redalyc.org/articulo.oa?id=42938349004 pt http://www.redalyc.org/revista.oa?id=429 Eclética Química application/pdf Universidade Estadual Paulista Júlio de Mesquita Filho Eclética Química (Brasil) Num.4 Vol.36