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Biology / Machine learning / Microarrays / Formal sciences / Bioinformatics / Probabilistic latent semantic analysis / Generative model / Latent Dirichlet allocation / Topic model / Statistics / Science / Statistical natural language processing


IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, Investigating Topic Models’ Capabilities in Expression Microarray Data Classification Manuele Bicego, Pietro Lovato, Alessandro Perina, Marianna Fasol
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Document Date: 2013-03-19 09:37:42


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City

Verona / Redmond / gene expression / Reading / Genova / /

Company

Neural Information Processing Systems / Supervised LDA / Microsoft / /

Country

Italy / Jordan / /

Currency

USD / /

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Facility

Masada / Digital Library / /

IndustryTerm

employed tool / cross-validation protocols / biological systems / finance / interpretable tool / energy / http /

OperatingSystem

L3 / /

Organization

Nat’l Academy / Pattern Analysis and Machine Intelligence / /

Person

P. Lovato / V / S. Powell / Alessandro Perina / Marianna Fasoli / A. von Deimling / J. Mesirov / H.F. Frierson Jr. / Nat / Massimo Delledonne / C. Bloomfield / C. Moskaluk / T. Batchelor / P. Black / Mario Pezzotti / U. Castellani / V / J. Downing / M. Caligiuri / Annalisa Polverari / G. Stolovitzky / E. Lander / Vittorio Murino Abstract / G. Hampton / A. Califano / H. Coller / H. Lapp / S. Pomeroy / P. Spellman / V / T. Golub / M. Loh / A. Perina / V / P. Schultz / D. Louis / /

Position

single model for all classes / General / model data log-likelihood / linguist / /

ProvinceOrState

Washington / /

PublishedMedium

Machine Learning / Cancer Research / Nature Genetics / /

Technology

Genomics / BIOINFORMATICS / Machine Learning / Image Processing / cross-validation protocols / learning algorithm / DNA Chip / gene expression / Data Mining / Digital Object Identifier / /

URL

http /

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