Journal ArticleDOI
Minimum redundancy feature selection from microarray gene expression data.
Chris Ding,Hanchuan Peng +1 more
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How to selecting a small subset out of the thousands of genes in microarray data is important for accurate classification of phenotypes.Abstract:
How to selecting a small subset out of the thousands of genes in microarray data is important for accurate classification of phenotypes. Widely used methods typically rank genes according to their ...read more
Citations
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Journal ArticleDOI
Feature weight estimation for gene selection: a local hyperlinear learning approach.
TL;DR: Experiments on both synthetic and real-world datasets demonstrate the superior performance of the proposed feature selection method combined with supervised learning in three aspects: high classification accuracy, excellent robustness to noise and good stability using to various classification algorithms.
Journal ArticleDOI
Feature Selection: A Practitioner View
TL;DR: A near comprehensive list of problems that have been solved using feature selection across technical and commercial domain is produced and can serve as a valuable tool to practitioners across industry and academia.
Journal ArticleDOI
Fast feature selection aimed at high-dimensional data via hybrid-sequential-ranked searches
TL;DR: This work examines the performance of two hybrid strategies that directly search on a ranked list of features and compares them with two widely used algorithms, the fast correlation based filter and sequential forward selection.
Journal ArticleDOI
Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy Approach
TL;DR: Experimental results show that W-QEISS has the capability of evolving a rich and diverse set of Pareto-efficient solutions, and that their availability helps in: 1) studying the tradeoff between multiple measures of classification performance and 2) understanding the relative importance of each feature.
Proceedings Article
Selecting Diverse Features via Spectral Regularization
TL;DR: This work proposes several spectral regularizers that capture a notion of diversity of features and result in approximately submodular functions, which can then be maximized by efficient greedy and local search algorithms, with provable guarantees.
References
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Journal ArticleDOI
Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.
Todd R. Golub,Todd R. Golub,Donna K. Slonim,Pablo Tamayo,Christine Huard,Michelle Gaasenbeek,Jill P. Mesirov,Hilary A. Coller,Mignon L. Loh,James R. Downing,Michael A. Caligiuri,Clara D. Bloomfield,Eric S. Lander +12 more
TL;DR: A generic approach to cancer classification based on gene expression monitoring by DNA microarrays is described and applied to human acute leukemias as a test case and suggests a general strategy for discovering and predicting cancer classes for other types of cancer, independent of previous biological knowledge.
Journal ArticleDOI
Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling
Ash A. Alizadeh,Michael B. Eisen,R. Eric Davis,Izidore S. Lossos,Andreas Rosenwald,Jennifer C. Boldrick,Hajeer Sabet,Truc Tran,Xin Yu,John Powell,Liming Yang,Gerald E. Marti,Troy Moore,James I. Hudson,Li-Sheng Lu,David B. Lewis,Robert Tibshirani,Gavin Sherlock,Wing C. Chan,Timothy C. Greiner,Dennis D. Weisenburger,James O. Armitage,Roger A. Warnke,Ronald Levy,Wyndham H. Wilson,M. R. Grever,John C. Byrd,David Botstein,Patrick O. Brown,Louis M. Staudt +29 more
TL;DR: It is shown that there is diversity in gene expression among the tumours of DLBCL patients, apparently reflecting the variation in tumour proliferation rate, host response and differentiation state of the tumour.
Journal ArticleDOI
Wrappers for feature subset selection
Ron Kohavi,George H. John +1 more
TL;DR: The wrapper method searches for an optimal feature subset tailored to a particular algorithm and a domain and compares the wrapper approach to induction without feature subset selection and to Relief, a filter approach tofeature subset selection.
Journal ArticleDOI
A comparison of methods for multiclass support vector machines
Hsu Chih-Wei,Chih-Jen Lin +1 more
TL;DR: Decomposition implementations for two "all-together" multiclass SVM methods are given and it is shown that for large problems methods by considering all data at once in general need fewer support vectors.
Journal ArticleDOI
Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays.
Uri Alon,Naama Barkai,Daniel A. Notterman,Kurt C. Gish,S. Ybarra,David H. Mack,A. J. Levine,A. J. Levine +7 more
TL;DR: In this paper, a two-way clustering algorithm was applied to both the genes and the tissues, revealing broad coherent patterns that suggest a high degree of organization underlying gene expression in these tissues.