ACC | 96.94% |
Precision | 96.27% |
Recall | 96.27% |
F1 score | 0.9627 |
AUC | 0.9701 |
Forecast | ||
---|---|---|
Normal data | Fault data | |
Normal data | 15611 | 14 |
Fault data | 14 | 361 |
Improved random forest algorithm based on fault ratio |
Step1: The training samples were randomly put back from the data set, and were extracted for n times in total to obtain n independent training sets with repeated elements. Step2: The n decision trees are trained on different training sets. Step3: The sample category labels corresponding to N decision trees were analyzed, and the final voting induction was carried out by combining the improved voting decision method based on fault ratio. |
aa_000 | 1.454301e+05 | 1.454301e+05 |
ac_000 | 7.767625e+08 | 7.724678e+08 |
ad_000 | 3.504525e+07 | 3.504515e+07 |
ae_000 | 1.581479e+02 | 1.581420e+02 |
af_000 | 2.053871e+02 | 2.053753e+02 |
... | ... | |
ee_007 | 1.718666e+06 | 1.718366e+06 |
ee_008 | 4.472145e+05 | 4.469894e+05 |
ee_009 | 4.721249e+04 | 4.720424e+04 |
ef_000 | 4.268570e+00 | 4.268529e+00 |
eg_000 | 8.628043e+00 | 8.627929e+00 |