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

Table 2

Attributes, instances, defective, and nondefective modules of each utilized dataset.

S. no.	Datasets	No. of attributes	No. of instances	No. of defective modules		No. of nondefective modules		Data type
1	AR1	30	121	9	7.4%	112	92.6%	Numerical
2	AR3	30	63	8	12.7%	55	87.3%	Numerical
3	CM1	22	498	49	9.8%	449	90.2%	Numerical
4	KC2	22	522	107	20.5%	415	79.5%	Numerical
5	KC3	40	194	36	18.6%	158	81.4%	Numerical
6	MW1	41	403	31	8.0%	372	92.0%	Numerical
7	PC1	22	1109	77	6.9%	1032	93.1%	Numerical
8	PC2	41	5589	23	0.5%	5566	99.5%	Numerical
9	PC3	41	1563	160	10.1%	1403	89.9%	Numerical
10	PC4	41	1458	178	12.2%	1280	87.8%	Numerical