Fig. 4

Establishment of classification models for differentiating the two lactylation activity phenotypes. (A–H) Feature gene selection using four classification algorithms: (A) LogitBoost, (C) NaïveBayes, (E) RandomForest, and (G) SVM, and ROC analysis to evaluate the performance of the (B) LogitBoost, (D) NaïveBayes, (F) RandomForest, and (H) SVM models in differentiating the two lactylation activity phenotypes in the training, test, and total sets. (I) Venn diagram displaying the intersection of the feature genes (ALDOB, CCT5, EP300, PFKP, PPIA, and SIRT1) extracted from the four classification models.