BMC Medical Informatics and Decision Making

Table 7 Final AdaBoost model scores

From: Ada-WHIPS: explaining AdaBoost classification with applications in the health sciences

		Undiscretised: used by		Discretised: used by
		Ada-WHIPS & LORE		Anchors
Data	ntree	Accuracy	κ	Accuracy	κ
SAMME
Breast cancer	200	0.98	0.96	0.96	0.92
Cardiotocography	800	0.94	0.84	0.89	0.70
Diabetic retinopathy	1000	0.68	0.36	0.66	0.33
Cleveland heart	200	0.77	0.52	0.80	0.59
Mental health survey ’16	200	0.88	0.76	0.88	0.75
Mental health survey ’14	200	0.83	0.65	0.81	0.62
Hospital readmission	800	0.62	0.22	0.60	0.18
Thyroid	1200	0.97	0.92	0.80	0.45
Understanding society	600	0.64	0.13	0.61	0.14
SAMME.R
Breast cancer	1000	0.98	0.96	0.95	0.90
Cardiotocography	1600	0.94	0.82	0.88	0.67
Diabetic retinopathy	200	0.69	0.38	0.65	0.30
Cleveland heart	400	0.76	0.50	0.82	0.63
Mental health survey ’16	800	0.87	0.73	0.86	0.72
Mental health survey ’14	200	0.80	0.60	0.81	0.63
Hospital readmission	200	0.62	0.22	0.63	0.23
Thyroid	1600	0.97	0.92	0.76	0.37
Understanding society	200	0.62	0.13	0.62	0.15

Accuracy and Cohen’s kappa on Held Out Data

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