Fig. 6
From: Machine learning model for early diagnosis of breast cancer based on PiRNA expression with CA153
XGBoost Model Simplification. (A) Random forest for significant contributions of three piRNAs and CA153 to model predictions; (B,C) Pearson correlation (B) and LASSO regression analysis (C) for collinearity analysis of three piRNAs and CA153; (D–F) ROC curves for XGBoost algorithm in the training cohort (D), cross-validation (E) and validation cohort (F); (G,H) PR curve (G) and DCA (H) for XGBoost algorithm in the training cohort (left) and validation cohort (right); (I) SHAP interpretation of the model constructed by the XGBoost algorithm.
