Download Feature Selection and Ensemble Methods for Bioinformatics: by Oleg Okun PDF

By Oleg Okun

Computing device studying is the department of man-made intelligence whose target is to boost algorithms that upload studying services to pcs. Ensembles are an essential component of laptop studying. a regular ensemble contains a number of algorithms acting the duty of prediction of the category label or the measure of sophistication club for a given enter provided as a suite of measurable features, referred to as positive aspects. characteristic choice and Ensemble tools for Bioinformatics: Algorithmic type and Implementations deals a different point of view on desktop studying features of microarray gene expression established melanoma type. This multidisciplinary textual content is on the intersection of machine technology and biology and, consequently, can be utilized as a reference booklet by way of researchers and scholars from either fields. every one bankruptcy describes the method of set of rules layout from starting to finish and goals to notify readers of top practices to be used of their personal learn.

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Extra resources for Feature Selection and Ensemble Methods for Bioinformatics: Algorithmic Classification and Implementations

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Wu, & V. ), The top ten algorithms in data mining (pp. 151-162). Boca Raton, FL: Chapman & Hall/CRC Press. , & Tibshirani, R. (2001). Missing value estimation methods for DNA microarrays. Bioinformatics (Oxford, England), 17(6), 520–525. , & Bengio, Y. (2002). K-local hyperplane and convex distance nearest neighbor algorithms. In Dietterich, T. , & Ghahramani, Z. ), Advances in Neural Information Processing Systems, 14 (pp. 985–992). Cambridge, MA: MIT Press. , Makedon, F. , Ford, J. , & Pearlman, J.

Norvig, P. (2003). ). Upper Saddle River, NJ: Pearson Education. , Makedon, F. , Ford, J. , & Pearlman, J. (2005). HykGene: a hybrid approach for selecting marker genes for phenotype classification using microarray gene expression data. Bioinformatics (Oxford, England), 21(8), 1530–1537. , & Dougherty, E. R. (2003). Binarization of microarray data on the basis of a mixture model. Molecular Cancer Therapeutics, 2(7), 679–684. ENDNOTES 1 Let us consider a simple example from medical diagnosis, borrowed from (Russell & Norvig, 2003) and showing how to calculate P (B|A) .

Oxford, UK: Oxford University Press. , & Norvig, P. (2003). ). Upper Saddle River, NJ: Pearson Education. , Makedon, F. , Ford, J. , & Pearlman, J. (2005). HykGene: a hybrid approach for selecting marker genes for phenotype classification using microarray gene expression data. Bioinformatics (Oxford, England), 21(8), 1530–1537. , & Dougherty, E. R. (2003). Binarization of microarray data on the basis of a mixture model. Molecular Cancer Therapeutics, 2(7), 679–684. ENDNOTES 1 Let us consider a simple example from medical diagnosis, borrowed from (Russell & Norvig, 2003) and showing how to calculate P (B|A) .

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