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Table 4 F-measure values for multi-class data set (LVH), cross-validation = 10 and K NN  = 5

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
A B C D E F G H I J K
Random Forest PAMAP2 0.44 0.62 0.67 0.65 0.72 0.64 0.73 0.74 0.77 0.75 0.68
Landstat 0.84 0.88 0.91 0.9 0.92 0.89 0.93 0.94 0.96 0.94 0.91
Mashup 0.28 0.34 0.38 0.36 0.51 0.35 0.54 0.54 0.58 0.56 0.41
SIDO 0.87 0.91 0.92 0.92 0.93 0.91 0.94 0.95 0.97 0.95 0.92
Naïve Bayes PAMAP2 0.4 0.6 0.63 0.62 0.68 0.61 0.71 0.72 0.75 0.73 0.64
Landstat 0.82 0.85 0.87 0.86 0.91 0.85 0.92 0.92 0.93 0.92 0.89
Mashup 0.25 0.31 0.34 0.33 0.48 0.32 0.52 0.52 0.55 0.53 0.37
SIDO 0.84 0.87 0.88 0.88 0.91 0.87 0.92 0.92 0.93 0.93 0.9
AdaBoostM1 PAMAP2 0.42 0.61 0.65 0.64 0.71 0.63 0.74 0.75 0.76 0.75 0.66
Landstat 0.83 0.87 0.89 0.88 0.92 0.87 0.93 0.93 0.94 0.93 0.9
Mashup 0.26 0.32 0.36 0.35 0.5 0.34 0.52 0.53 0.57 0.55 0.39
SIDO 0.86 0.9 0.9 0.89 0.92 0.89 0.94 0.94 0.95 0.94 0.91
MultiLayer Perceptron PAMAP2 0.41 0.6 0.64 0.63 0.7 0.62 0.73 0.74 0.75 0.74 0.65
Landstat 0.83 0.86 0.88 0.87 0.92 0.86 0.92 0.92 0.94 0.92 0.9
Mashup 0.26 0.31 0.35 0.34 0.49 0.33 0.53 0.53 0.56 0.54 0.38
SIDO 0.85 0.89 0.89 0.88 0.91 0.88 0.92 0.93 0.94 0.94 0.9
Overall average 0.59 0.67 0.70 0.69 0.76 0.68 0.78 0.78 0.80 0.79 0.71