Table 3.

Results of each algorithm model after PCA dimensionality reduction

	TP	FN	FP	TN	Accuracy	Sensitivity	Specificity
PCA + DT	24	7	9	18	72.41%	77.42%	66.67%
PCA + Bayes	12	11	9	26	65.52%	52.17%	74.29%
PCA + BPnet	16	10	5	27	74.14%	61.54%	84.38%
PCA + K-NN	17	10	7	24	70.69%	62.96%	77.42%
PCA + SVM	16	10	9	23	67.24%	61.54%	71.88%
PCA + RF	24	4	7	23	81.03%	85.71%	76.67%
PCA + GBDT	21	5	5	27	82.76%	80.77%	84.38%

*FN False Negative, FP False Positive, TN True Negative, TP True Positive