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

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.


Published in:
Breast Cancer Research, 12, -
Year:
2010
Keywords:
Laboratories:




 Record created 2011-12-16, last modified 2018-03-17


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