The effect of reduction in cross-validation intervals on the performance of multifactor dimensionality reduction.

@article{Motsinger2006TheEO,
  title={The effect of reduction in cross-validation intervals on the performance of multifactor dimensionality reduction.},
  author={Alison A. Motsinger and Marylyn DeRiggi Ritchie},
  journal={Genetic epidemiology},
  year={2006},
  volume={30 6},
  pages={546-55}
}
Multifactor Dimensionality Reduction (MDR) was developed to detect genetic polymorphisms that present an increased risk of disease. Cross-validation (CV) is an important part of the MDR algorithm, as it prevents over-fitting and allows the predictive ability of a model to be evaluated. CV is a computationally intensive step in the MDR algorithm. Traditionally, MDR has been implemented using 10-fold CV. In order to reduce computation time and therefore allow MDR analysis to be applied to larger… CONTINUE READING

From This Paper

Topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 27 extracted citations

Activity Classification in Independent Living Environment with JINS MEME Eyewear

2018 IEEE International Conference on Pervasive Computing and Communications (PerCom) • 2018
View 1 Excerpt

Similar Papers

Loading similar papers…