Ten lectures on wavelets
A practical approach to feature selection
ML92 Proceedings of the ninth international workshop on Machine learning
An introduction to wavelets
Selection of relevant features and examples in machine learning
Artificial Intelligence - Special issue on relevance
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Feature selection for high-dimensional genomic microarray data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
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Data mining is a boon to many fields like bioinformatics for processing a vast amount of data. In our previous paper, we proposed a novel feature selection method for microarray data classification using Wavelet Power Spectrum (WPS). In this paper, we present optimisation techniques to improve the quality of the features thus selected and to select |tight genes| from various cancer microarrays. The results show that |tight genes| thus selected were more qualitative and could be used for a wide variety of data sets. Also, |tight genes| thus selected in this mining process could be used with any existing classification approach.