Extended Data Fig. 2: Model performance in 5-fold cross validation (CV) of the 450 K training set. | Nature Cancer

Extended Data Fig. 2: Model performance in 5-fold cross validation (CV) of the 450 K training set.

From: crossNN is an explainable framework for cross-platform DNA methylation-based classification of tumors

Extended Data Fig. 2

Model performance in 5-fold cross validation (5xCV) of the 450 K training set. (a) Accuracy for each individual methylation class and methylation class family (MCF) during 5-fold CV. (b) Overall accuracy of the crossNN model in 5xCV of the training set. Validation folds were subsampled at the indicated rate to simulate sparse methylomes. Random sampling and 5xCV were repeated ten times at each sample rate. Box plots indicate median accuracy (center line), inter-quartile range (box) and 1.5fold interquartile range (whiskers). Outliers are indicated by dots.

Source data

Back to article page