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Benchmarking machine learning models for the analysis of genetic data using FRESA.CAD Binary Classification Benchmarking

  • de Velasco Oriol J
  • Martinez-Torteya A
  • Trevino V
  • et al.
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Abstract

Machine learning models have proven to be useful tools for the analysis of genetic data. However, with the availability of a wide variety of such methods, model selection has become increasingly difficult, both from the human and computational perspective. We present the R package FRESA.CAD Binary Classification Benchmarking that performs systematic comparisons between a collection of representative machine learning methods for solving binary classification problems on genetic datasets. FRESA.CAD Binary Benchmarking demonstrates to be a useful tool over a variety of binary classification problems comprising the analysis of genetic data showing both quantitative and qualitative advantages over similar packages.

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de Velasco Oriol, J., Martinez-Torteya, A., Trevino, V., Alanis, I., Vallejo, E., & Tamez-Pena, J. G. (2019). Benchmarking machine learning models for the analysis of genetic data using FRESA.CAD Binary Classification Benchmarking. https://doi.org/10.1101/733675

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