Investigating Tree Family Machine Learning Techniques for a Predictive System to Unveil Software Defects

Table 18

MCC analysis by each TF-ML technique on individual dataset.

Technique	AR1	AR3	CM1	KC2	KC3	MW1	PC1	PC2	PC3	PC4
CDT	?	?	−0.0297	0.4329	0.2433	0.1952	0.3565	?	0.0588	0.4091
CS-Forest	0.1801	0.3562	0.2032	0.5022	?	0.2361	0.3633	0.0832	0.3916	0.2811
DS	−0.0367	0.4872	?	0.4285	0.3309	0.2174	?	?	?	?
Forest-PA	−0.0259	0.3624	−0.0148	0.4294	−0.0598	−0.0144	0.2669	?	0.0978	0.4271
HT	?	0.2841	?	0.4299	−0.0344	?	?	?	?	0.1425
J48	0.1996	0.4273	0.0493	0.4082	0.2567	0.2374	0.328	?	0.2931	0.5148
LMT	−0.0259	0.2917	0.0178	0.4505	0.2056	0.318	0.0691	−0.0009	0.0286	0.4581
RF	−0.0452	0.6236	0.088	0.4459	0.1886	0.2635	0.3908	?	0.2828	0.4873
RT	0.1781	0.4273	0.147	0.3755	0.0174	0.1575	0.3215	0.0385	0.1955	0.3732
REP-T	?	0.2029	-0.0333	0.3547	0.1461	0.0518	0.363	?	0.1124	0.4501