Table 5: ML algorithms applied in observed works.

Algorithm		Papers	N of papers
Trees and Boosting	RF Random Forest	[16, 18, 19, 21, 23, 24, 29, 30, 34, 35, 38, 42]	12	28
	DT Decision trees	[13-19, 27, 28, 37, 38, 40]	8
	Gradient boosting DT	[26, 30, 34]	3
	AdaBoost	[19, 24, 29, 38]	4
	LogitBoost	[32]	1
ANN	MLP Multi-layer perceptron	[13, 19, 27, 30, 33, 36, 37]	7	12
	Other	[27, 38, 41, 42]	5
	LogitBoost	[32]	1
LR Logistic Regression		[13, 18, 29-31, 34, 39]	7	7
SVM Support Vector Machines		[18-20, 37, 41-43]	7	7
Others		[17, 27, 35, 37, 38, 41]	6	6
Naïve Bayes (NB)		[19, 24, 29, 38, 39]	5	5
k-NN k-Nearest Neighbors		[38, 41]	2	2