Predict the Entrepreneurial Intention of Fresh Graduate Students Based on an Adaptive Support Vector Machine Framework

Table 6

Performance of RF-CSCA-SVM on different sizes of feature subset.

Size of feature subset	ACC	Sensitivity	Specificity	MCC
1	0.6600(0.0625)	0.6357(0.0473)	0.7605 (0.1534)	0.3265(0.1420)
2	0.7300(0.0637)	0.7399(0.0889)	0.7323 (0.0719)	0.4600(0.1313)
3	0.7767 (0.0802)	0.7815 (0.1025)	0.7862 (0.0850)	0.5560 (0.1621)
4	0.7567 (0.0649)	0.7701 (0.0750)	0.7553 (0.1014)	0.5136 (0.1398)
5	0.8400 (0.0439)	0.8597 (0.0570)	0.8347 (0.0862)	0.6850 (0.0873)
6	0.7733 (0.0872)	0.8168 (0.1084)	0.7413 (0.1080)	0.5529 (0.1831)
7	0.7867 (0.0849)	0.8482 (0.1187)	0.7381 (0.0786)	0.5819 (0.1791)
8	0.7800 (0.0706)	0.8307 (0.0634)	0.7464 (0.1101)	0.5710 (0.1360)
9	0.6967 (0.1024)	0.7282 (0.1066)	0.6688 (0.1140)	0.3928 (0.2073)