Journal of Big Data

Table 3 F-measure values for multi-class data set (LVH), cross-validation = 5 and K_NN = 3

From: Improved classification of large imbalanced data sets using rationalized technique: Updated Class Purity Maximization Over_Sampling Technique (UCPMOT)

Classifier	Data set	Over_sampling techniques
Classifier	Data set	A	B	C	D	E	F	G	H	I	J	K
Random Forest	PAMAP2	0.43	0.63	0.67	0.65	0.7	0.64	0.74	0.76	0.77	0.75	0.67
	Landstat	0.84	0.87	0.87	0.86	0.9	0.85	0.91	0.95	0.96	0.93	0.9
	Mashup	0.26	0.33	0.36	0.35	0.5	0.34	0.53	0.54	0.58	0.55	0.4
	SIDO	0.86	0.89	0.9	0.89	0.92	0.89	0.93	0.94	0.95	0.93	0.91
Naïve Bayes	PAMAP2	0.39	0.58	0.61	0.59	0.64	0.59	0.7	0.71	0.74	0.74	0.62
	Landstat	0.81	0.84	0.85	0.85	0.88	0.84	0.91	0.91	0.92	0.91	0.86
	Mashup	0.24	0.3	0.33	0.32	0.46	0.31	0.5	0.51	0.54	0.53	0.36
	SIDO	0.83	0.86	0.87	0.85	0.89	0.85	0.91	0.91	0.92	0.92	0.89
AdaBoostM1	PAMAP2	0.4	0.6	0.64	0.63	0.69	0.62	0.73	0.73	0.75	0.74	0.65
	Landstat	0.82	0.86	0.86	0.86	0.91	0.86	0.92	0.93	0.93	0.92	0.89
	Mashup	0.25	0.32	0.35	0.34	0.47	0.33	0.51	0.52	0.56	0.54	0.38
	SIDO	0.85	0.88	0.89	0.88	0.9	0.93	0.92	0.93	0.94	0.93	0.9
MultiLayer Perceptron	PAMAP2	0.4	0.59	0.63	0.63	0.68	0.62	0.73	0.73	0.74	0.74	0.64
	Landstat	0.81	0.85	0.86	0.85	0.9	0.85	0.91	0.92	0.92	0.92	0.88
	Mashup	0.25	0.31	0.34	0.33	0.49	0.32	0.52	0.53	0.55	0.53	0.37
	SIDO	0.84	0.87	0.88	0.87	0.9	0.87	0.9	0.92	0.93	0.92	0.9
Overall average		0.58	0.66	0.68	0.67	0.74	0.67	0.77	0.77	0.79	0.78	0.70

Italic values indicate highest result

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