ShinyLearner: A containerized benchmarking tool for machine-learning classification of tabular data.

ABSTRACT:

Background

Classification algorithms assign observations to groups based on patterns in data. The machine-learning community have developed myriad classification algorithms, which are used in diverse life science research domains. Algorithm choice can affect classification accuracy dramatically, so it is crucial that researchers optimize the choice of which algorithm(s) to apply in a given research domain on the basis of empirical evidence. In benchmark studies, multiple algorithms are applied to multiple datasets, and the researcher examines overall trends. In addition, the researcher may evaluate multiple hyperparameter combinations for each algorithm and use feature selection to reduce data dimensionality. Although software implementations of classification algorithms are widely

SUBMITTER: Piccolo SR 

PROVIDER: S-EPMC7131989 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature