Table 4.

Results achieved on the training set for the vowel /a/

Algorithm	Sensibility (%)	Specificity (%)	Accuracy (%)	Precision (%)	F1-score (%)	AUC
Naive Bayes [25]	92.42	28.79	60.61	56.48	70.11	0.801
Bayes Net [25]	78.79	68.18	73.48	71.23	74.82	0.775
SVM [6]	95.45	93.94	94.70	94.03	94.74	0.947
SGD [3]	95.45	100.00	97.73	100.00	97.67	0.977
Ibk [2]	100.00	100.00	100.00	100.00	100.00	1.000
LWL [14]	80.30	65.15	72.73	69.74	74.65	0.908
Adaboost [12]	78.79	93.94	86.36	92.86	85.25	0.952
Bagging [12]	89.39	87.88	88.64	88.06	88.72	0.958
OneR [19]	75.00	86.36	81.15	82.35	78.50	0.750
Decision Table [26]	75.76	71.21	73.48	72.46	74.07	0.753
J48 [41]	98.48	96.97	97.73	97.01	97.74	0.993
Random Forest [49]	100.00	100.00	100.00	100.00	100.00	1.000