A Facile machine learning multi-classification model for Streptococcus agalactiae clonal complexes

Table 2 Effectiveness evaluation results of S&A CCs prediction model

Index	AUC	Accuracy	precision	sensitivity	specificity	PPV	NPV
CC1	0.9205	0.9184	0.5833	0.7	0.9432	0.5833	0.9651
CC10	0.9777	0.9694	0.8462	0.9167	0.9767	0.8462	0.9882
CC12	1	1	1	1	1	1	1
CC17	0.9819	0.949	0.7857	0.8462	0.9647	0.7857	0.9762
CC19	0.9484	0.9388	0.9474	0.7826	0.9867	0.9474	0.9367
CC23	0.9744	0.9082	0.5625	0.8182	0.9195	0.5625	0.9756
CC24	0.9613	0.9592	0.7778	0.7778	0.9775	0.7778	0.9775
Others	0.6021	0.8878	0	0	0.9667	0	0.9158
Mean	0.9212	0.7653	0.6879	0.7302	0.9669	0.6879	0.9669

CCs clonal complexes, AUC area under the curve, PPV positive predictive value, NPV negative predictive value
^*S&A model, the CCs prediction model based on serotype and antibiotic resistance of S. agalactiae

ISSN: 1476-0711