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Fig. 2 | BMC Cancer

Fig. 2

From: Artificial neural network models to predict nodal status in clinically node-negative breast cancer

Fig. 2

Model selection and internal validation strategies. Internal validation was performed by 4-fold cross-validation, which was repeated five times. Each round of cross-validation involved partitioning the data into a test set and a derivation set. The model selection was carried out for each of the derivation sets, independent of the corresponding test set, and was aimed to minimize information leakage. Model selection strategy was based on a 5-fold cross-validation, which was repeated seven times. Abbreviations: D, Different parts of the derivation set in each round of cross-validation. T, The test set in each round of cross-validation

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