Feature selection for high-dimensional genomic microarray data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Iteratively Selecting Feature Subsets for Mining from High-Dimensional Databases
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
IEEE Transactions on Information Technology in Biomedicine
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Markov blanket filtering based on discretized features (MBF) has been proposed as a feature selection strategy. Critical evaluation of MBF has demonstrated its contradictory and counterintuitive nature, which results in undesirable properties for small sample size applications such as classification based on microarray gene expression data.