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Feature selection from microarray data has become an ever evolving area of research. Numerous techniques have widely been applied for extraction of genes which are expressed differentially in microarray data. Some of these comprise of studies related to fold-change approach, classical t-statistics and modified t-statistics. It has been found that the gene lists returned by these methods are dissimilar...
In real world applications, there are great many of DNA expressed microarray data, many supervised classification algorithms such as decision tree, KNN and SVM in the machine learning field have been introduced for microarray data classification. However, in real worlds, the labeled examples, especially gene expression data examples are often very difficult and expensive to obtain. The traditional...
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