Scalable Feature Selection in High-Dimensional Data Based on GRASP

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Scalable Feature Selection in High-Dimensional Data Based on GRASP

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im März 2015 veröffentlichter wissenschaftlicher Artikel

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wetenschappelijk artikel

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наукова стаття, опублікована в березні 2015

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Scalable Feature Selection in High-Dimensional Data Based on GRASP

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Scalable Feature Selection in High-Dimensional Data Based on GRASP

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Scalable Feature Selection in High-Dimensional Data Based on GRASP

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Scalable Feature Selection in High-Dimensional Data Based on GRASP

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Scalable Feature Selection in High-Dimensional Data Based on GRASP

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Scalable Feature Selection in High-Dimensional Data Based on GRASP

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P1476

Scalable Feature Selection in High-Dimensional Data Based on GRASP

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P2093

Alireza Mohebalhojeh

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Mohsen Moshki

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Peyman Kabiri

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P2860

Peakbin selection in mass spectrometry data using a consensus approach with estimation of distribution algorithms.

Wrapper feature selection for small sample size data driven by complete error estimates.

Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy.

Normalized mutual information feature selection.

Combining functional networks and sensitivity analysis as wrapper method for feature selection

A NOVEL EMBEDDED FEATURE SELECTION METHOD: A COMPARATIVE STUDY IN THE APPLICATION OF TEXT CATEGORIZATION

LEARNING WITH GENE ONTOLOGY ANNOTATION USING FEATURE SELECTION AND CONSTRUCTION

A THREE-STAGE FEATURE SELECTION USING QUADRATIC PROGRAMMING FOR CREDIT SCORING

SELECTION OF NUMERICAL AND NOMINAL FEATURES BASED ON PROBABILISTIC DEPENDENCE BETWEEN FEATURES

Feature selection for the naive bayesian classifier using decision trees

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283-296

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scholarly article

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10.1080/08839514.2015.1004616

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P433

http://www.w3.org/2001/XMLSchema#string

P478

http://www.w3.org/2001/XMLSchema#string

P577

2015-03-16T00:00:00Z

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