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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Liu, Y. (2007). Cancer Identification Based on DNA Microarray Data. In: Washio, T., et al. Emerging Technologies in Knowledge Discovery and Data Mining. PAKDD 2007. Lecture Notes in Computer Science(), vol 4819. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77018-3_17
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DOI: https://doi.org/10.1007/978-3-540-77018-3_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77016-9
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