To evaluate the classifiers performance, sensitivity, specificity, positive predictive value (PPV), negative predictive
value (NPV) and accuracy were used. All these measures can be calculated based on four values: true positive (TP),
number of images correctly classified as motorcycles; false positive (FP), the number of images wrongly classified as
motorcycles; false negative (FN), the number of images wrongly classified as non-motorcycles and true negative (TN),
the number of images correctly classified as non-motorcycles. Those values are defined in table 1.
To evaluate the classifiers performance, sensitivity, specificity, positive predictive value (PPV), negative predictivevalue (NPV) and accuracy were used. All these measures can be calculated based on four values: true positive (TP),number of images correctly classified as motorcycles; false positive (FP), the number of images wrongly classified asmotorcycles; false negative (FN), the number of images wrongly classified as non-motorcycles and true negative (TN),the number of images correctly classified as non-motorcycles. Those values are defined in table 1.
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