(Q34096995)

English

Detection of independent associations in a large epidemiologic dataset: a comparison of random forests, boosted regression trees, conventional and penalized logistic regression for identifying independent factors associated with H1N1pdm influenza in

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scholarly article

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Europe PubMed Central

PubMed publication ID

31 July 2017

Detection of independent associations in a large epidemiologic dataset: a comparison of random forests, boosted regression trees, conventional and penalized logistic regression for identifying independent factors associated with H1N1pdm influenza in (English)

1 reference

Europe PubMed Central

PubMed publication ID

31 July 2017

logistic regression model

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based on heuristic

inferred from title

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based on heuristic

inferred from title

object named as

Fabrice Carrat

2

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author name string

Yohann Mansiaux

1

1 reference

Europe PubMed Central

PubMed publication ID

31 July 2017

publication date

26 August 2014

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Europe PubMed Central

PubMed publication ID

31 July 2017

BMC Medical Research Methodology

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Europe PubMed Central

PubMed publication ID

31 July 2017

14

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Europe PubMed Central

PubMed publication ID

31 July 2017

99

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Europe PubMed Central

PubMed publication ID

31 July 2017

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1 reference

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Classification with correlated features: unreliability of feature ranking and solutions

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A survey of variable selection methods in two Chinese epidemiology journals

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Risk factors for pandemic (H1N1) 2009 virus seroconversion among hospital staff, Singapore

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Permutation importance: a corrected feature importance measure

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Variable selection: current practice in epidemiological studies

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The mutual information: detecting and evaluating dependencies between variables.

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Identifiers

10.1186/1471-2288-14-99

1 reference

Europe PubMed Central

PubMed publication ID

31 July 2017

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PMC publication ID

1 reference

Europe PubMed Central

PubMed publication ID

31 July 2017

PubMed publication ID

1 reference

Europe PubMed Central

PubMed publication ID

31 July 2017

ResearchGate publication ID

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