Machine learning framework with feature selection approaches for thyroid disease classification and associated risk factors identification

Journal of Electrical Systems and Information Technology

Table 4 Classification result of all ML models using all features

Algorithm	Accuracy (%)	Precision (%)	Recall (%)	F1-score (%)
KNN	94	63	80	67
RF	98	82	74	77
DT	97	77	71	74
SVM	76	53	73	50
AB	98	85	76	80
GB	98	80	80	80

Algorithm	Accuracy (%)	Precision (%)	Recall (%)	F1-score (%)
KNN	94	63	80	67
RF	98	82	74	77
DT	97	77	71	74
SVM	76	53	73	50
AB	98	85	76	80
GB	98	80	80	80

Algorithm	Accuracy (%)	Precision (%)	Recall (%)	F1-score (%)
KNN	94	63	80	67
RF	98	82	74	77
DT	97	77	71	74
SVM	76	53	73	50
AB	98	85	76	80
GB	98	80	80	80

Algorithm	Accuracy (%)	Precision (%)	Recall (%)	F1-score (%)
KNN	94	63	80	67
RF	98	82	74	77
DT	97	77	71	74
SVM	76	53	73	50
AB	98	85	76	80
GB	98	80	80	80