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.
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