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  4. Effect of training-sample size and classification difficulty on the accuracy of genomic predictors
 
research article

Effect of training-sample size and classification difficulty on the accuracy of genomic predictors

Popovici, Vlad
•
Chen, Weijie
•
Gallas, Brandon G.
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2010
Breast Cancer Research

Introduction: As part of the MicroArray Quality Control (MAQC)-II project, this analysis examines how the choice of univariate feature-selection methods and classification algorithms may influence the performance of genomic predictors under varying degrees of prediction difficulty represented by three clinically relevant endpoints.

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