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. 2018 Nov 30;19(Suppl 15):438. doi: 10.1186/s12859-018-2414-9

Table 2.

Optimization of the machine learning classifiers

Classification accuracy on the MANY dataset Classification accuracy on the independent DC dataset
Bagging 0.92 0.73
Random Forest 0.92 0.74
Adaptive Boosting 0.92 0.74
Gradient Boosting 0.93 0.74
Neural Network 0.91 0.75

The maximum accuracy reached by optimizing the settings is reported by each classifier for the Many (as average over the 10-fold cross-validation) and the DC datasets