Rotating Machinery Fault Diagnosis for Imbalanced Data Based on Fast Clustering Algorithm and Support Vector Machine

Table 2

Evaluation indexes comparisons of fault diagnosis model and other models.

Proportion of the data set	10 : 150	15 : 150	40 : 150	50 : 150	80 : 150	100 : 150
-mean of fault diagnosis model	0.94	0.95	0.96	0.94	0.92	0.88
-mean of fault diagnosis model	0.54	0.65	0.86	0.85	0.88	0.86
-mean of FCA + BP	0.61	0.69	0.68	0.87	0.89	0.87
-mean of FCA + BP	0.16	0.28	0.48	0.77	0.86	0.84
-mean of FCA + RBF	0.92	0.93	0.92	0.90	0.91	0.89
-mean of FCA + RBF	0.47	0.59	0.78	0.79	0.87	0.86
-mean of RU + SVM	0.93	0.91	0.90	0.91	0.91	0.90
-mean of RU + SVM	0.50	0.54	0.75	0.81	0.86	0.88
-mean of SMOTE + SVM	0.85	0.91	0.92	0.92	0.92	0.91
-mean of SMOTE + SVM	0.36	0.55	0.78	0.83	0.88	0.89
-mean of SVM	0.60	0.68	0.85	0.87	0.92	0.89
-mean of SVM	0.16	0.28	0.69	0.77	0.88	0.87