Table 7.

Classification accuracy of ML algorithms for IoT oriented healthcare requirements.

Classification accuracy in 10 iterations using TF-IDF
Machine learning algorithm	1	2	3	4	5	6	7	8	9	10	Average classification accuracy
Hybrid	0.73	0.73	0.73	1.00	0.70	0.90	0.60	0.70	0.80	0.70	0.759
Ensemble	0.82	0.64	0.27	0.64	0.80	0.60	0.70	0.70	0.60	0.50	0.627
LR	0.82	0.64	0.27	0.64	0.80	0.60	0.70	0.70	0.60	0.50	0.627
SVM	0.82	0.64	0.27	0.64	0.80	0.60	0.70	0.70	0.60	0.50	0.627
MNB	0.82	0.64	0.27	0.64	0.80	0.60	0.70	0.70	0.60	0.50	0.627
KNN	0.82	0.55	0.45	0.64	0.80	0.70	0.70	0.70	0.50	0.60	0.646
RF	0.82	0.64	0.27	0.64	0.80	0.60	0.70	0.70	0.60	0.50	0.627