| Summary: | 碩士 === 雲林科技大學 === 資訊管理系碩士班 === 98 === Feature selection method will affect access to multiple categories of classification
accuracy, In this study, Filters feature selection methods combined with Wrapper, Using
support vector machines for classification. Cancer microarray data with a low number
of samples of high dimensional data gene, Therefore, the correct classification rate
calculation because of the large number of characteristics leading to long computing time. To
address this issue, Application of appropriate feature selection can not have the characteristics
of classified information removed, Contribute to classification calculation, This study Filters
feature selection methods combined with Wrapper, Filters for feature extraction in the use of BW
ratio, Wrapper using genetic algorithms, Wrapper using genetic algorithms, Finally using support
vector machine classifier, Using cross validation classification accuracy assessment. The results
show, Use Filters Wrapper feature selection methods combined, can reduce the number of
feature and increase the classification accuracy.
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