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Table 2 Overall classification accuracy, precision, recall, F-score results from the first bearing dataset using the RGBVI-CNN method with 40% to 70% training size

From: Connected Components-based Colour Image Representations of Vibrations for a Two-stage Fault Diagnosis of Roller Bearings Using Convolutional Neural Networks

Training size (%) Overall classification accuracy Overall precision Overall recall F-score
40 99.3% ± 0.7 99.2% ± 0.8 99.3% ± 0.6 99.3% ± 0.7
50 99.8% ± 0.1 99.8% ± 0.1 99.8% ± 0.1 99.8% ± 0.1
60 99.9% ± 0.1 99.9% ± 0.1 99.9% ± 0.1 99.9% ± 0.1
70 100% ± 0.0 100% ± 0.0 100% ± 0.0 100% ± 0.0