期刊名称：International Journal of Computer Systems Science and Engineering
印刷版ISSN：1307-430X
出版年度：2007
卷号：03
期号：03
页码：138-138
出版社：World Academy of Science, Engineering and Technology
摘要：There are several approaches in trying to solve the
Quantitative 1Structure-Activity Relationship (QSAR) problem.
These approaches are based either on statistical methods or on
predictive data mining. Among the statistical methods, one should
consider regression analysis, pattern recognition (such as cluster
analysis, factor analysis and principal components analysis) or partial
least squares. Predictive data mining techniques use either neural
networks, or genetic programming, or neuro-fuzzy knowledge. These
approaches have a low explanatory capability or non at all. This
paper attempts to establish a new approach in solving QSAR
problems using descriptive data mining. This way, the relationship
between the chemical properties and the activity of a substance
would be comprehensibly modeled.
关键词：association rules, classification, data mining,
Quantitative Structure - Activity Relationship.
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