Does Rational Selection of Training and Test Sets Improve the Outcome of QSAR Modeling?

@article{Martin2012DoesRS,
  title={Does Rational Selection of Training and Test Sets Improve the Outcome of QSAR Modeling?},
  author={Todd Martin and Paul Harten and Douglas M. Young and Eugene N. Muratov and Alexander Golbraikh and Hao Zhu and Alexander Tropsha},
  journal={Journal of chemical information and modeling},
  year={2012},
  volume={52 10},
  pages={2570-8}
}
Prior to using a quantitative structure activity relationship (QSAR) model for external predictions, its predictive power should be established and validated. In the absence of a true external data set, the best way to validate the predictive ability of a model is to perform its statistical external validation. In statistical external validation, the overall data set is divided into training and test sets. Commonly, this splitting is performed using random division. Rational splitting methods… CONTINUE READING

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