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Machine learning algorithm validation with a limited sample size

Fig 3

Gaussian noise classification accuracy distributions with different validation approaches.

K-Fold, Nested, Train/Test Split and two types of partially nested validation methods used. Thick lines show mean validation accuracy and dash-dot lines show 95% confidence intervals for 50 runs. A: SVM-RFE feature selection and SVM classification. B: t-test feature selection and logistic regression classification.

Fig 3

doi: https://doi.org/10.1371/journal.pone.0224365.g003