Abstract
In this study we perform wavelet transform on the analysis of DNA microarray data. A set of wavelet features is used to measure the change of gene expression profile. Then wavelet features are input to support vector machine (SVM) to classify DNA microarray data into different diagnostic classes. Experiments are carried out on six datasets of microarray data. On a wide range of data sets, our method displays a highly competitive accuracy in comparison to the best performance of other kinds of classification models.
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