| Literature DB >> 15720123 |
Feng Luan1, Ruisheng Zhang, Chunyan Zhao, Xiaojun Yao, Mancang Liu, Zhide Hu, Botao Fan.
Abstract
The support vector machine (SVM), as a novel type of learning machine, was used to develop a classification model of carcinogenic properties of 148 N-nitroso compounds. The seven descriptors calculated solely from the molecular structures of compounds selected by forward stepwise linear discriminant analysis (LDA) were used as inputs of the SVM model. The obtained results confirmed the discriminative capacity of the calculated descriptors. The result of SVM (total accuracy of 95.2%) is better than that of LDA (total accuracy of 89.8%).Entities:
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Year: 2005 PMID: 15720123 DOI: 10.1021/tx049782q
Source DB: PubMed Journal: Chem Res Toxicol ISSN: 0893-228X Impact factor: 3.739