On the Use of Neural Network Ensembles in QSAR and QSPR

@article{Agrafiotis2002OnTU,
  title={On the Use of Neural Network Ensembles in QSAR and QSPR},
  author={Dimitris K. Agrafiotis and Walter Cede{\~n}o and Victor S. Lobanov},
  journal={Journal of chemical information and computer sciences},
  year={2002},
  volume={42 4},
  pages={903-11}
}
Despite their growing popularity among neural network practitioners, ensemble methods have not been widely adopted in structure-activity and structure-property correlation. Neural networks are inherently unstable, in that small changes in the training set and/or training parameters can lead to large changes in their generalization performance. Recent research has shown that by capitalizing on the diversity of the individual models, ensemble techniques can minimize uncertainty and produce more… CONTINUE READING

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