Table 2.

The Machine learning classification methods and their performance accuracy as measured by the percentage of correctly classified records and the F-Measure that combines precision and recall.

S. No	Methods	Percent correct	F measure
1	J48	74.52	0.82
2	Naïve Bayes	55.91*	0.71
3	Lib SVM	73.71	0.77
4	MultiLayer Perceptron	71.16	0.77
5	Ada Boost ML	71.29	0.75
6	Bagging	73.02	0.78
7	Stacking	56.68*	0.72
8	Random forest	75.21	0.81
9	Logistic	69.34	0.76

The best performing j48 decision tree algorithm is shown in bold. The * sign depicts significantly underperforming statistic.