PMC:4331678 / 26992-27731 JSONTXT

{"target":"https://pubannotation.org/docs/sourcedb/PMC/sourceid/4331678","sourcedb":"PMC","sourceid":"4331678","source_url":"https://www.ncbi.nlm.nih.gov/pmc/4331678","text":"We use five-fold cross validation to investigate the performance of the algorithms in predicting protein function. More specifically, we divide each dataset into five disjoint folds. In each round, we take four folds as the training data and the remaining fold as the testing set, in which the proteins are considered as unlabeled and to be predicted. We record the results on the testing data to measure the performance. The parameters of the comparing methods are optimized via five-fold cross validation on the training data. Figure 1 gives the prediction performance of the comparing methods on the BP, CC, and MF functions of Yeast, respectively. The results on the other datasets are reported in Figures 1-3 of the Additional File 1.","tracks":[]}