Table 5.

Top five important risk factors in descending order for different ML algorithms based on the US population-based training samples in 10-fold internal statistical cross-validations

ML: random forest	ML: logistic regression	ML: adapt boosting	ML: linear model	ML: K-nearest neighbors	ML: linear discriminant	ML: quadratic discriminant	ML: MCMC GLMM
Number of biopsies	Number of first-degree relatives with breast cancer	Number of biopsies	Age	Number of biopsies	Age	Number of first-degree relatives with breast cancer	Number of biopsies
Age	Age	Age	Number of biopsies	Number of first-degree relatives with breast cancer	Number of biopsies	Number of biopsies	Age
Number of first-degree relatives with breast cancer	Number of biopsies	Number of first-degree relatives with breast cancer	Number of first-degree relatives with breast cancer	Age	Ethnicity	Age	Number of first-degree relatives with breast cancer
Age at menarche	Ethnicity	Age at menarche	Age at menarche	Ethnicity	Number of first-degree relatives with breast cancer	Ethnicity	Age at first live birth
Ethnicity	Age at first live birth	Ethnicity	Age at first live birth	Age at first live birth	Age at first live birth	Age at menarche	Age at menarche