Accuracy is defined as the ratio of correctly classified examples to all examples classified: Accuracy = TP + TN TP + TN + FP + FN Where TP = true positive, TN = true negative, FP = false positive, and FN = false negative.
The performance of each classifier was assessed by two measures: (i) Percentage of samples correctly classified (Accuracy) and (ii) F measure, which is the harmonic mean of precision and recall.
Table 3 Performance of classifiers on unseen P2P botnets Decision trees Random forests Bayesian network Classified Classified Accuracy Classified Classified Accuracy Classified Classified Accuracy malicious benign malicious benign malicious benign Zeus 2,696 55 98 % 2,717 34 98.76 % 2,660 91 96.69Nugache 42 7 85.71% 43 6 87.76% 48 1 97.96%.
Extensive experimental results on real-world datasets have validated our approach in terms of classifying accuracy and computational efficiency.
Through various experiments on MNIST variation datasets, FCCNN achieves classifying accuracy comparable to the state-of-the-art methods while requires significantly reduced training time.
For the Twist 1 sample set, the standard deviation of each dimension is relatively small and the sensitivity of classifying accuracy on T is reduced; however, when the T is selected as 200, the maximum classification accuracy is achieved.
Analysis was carried out for the classification of patients with PCA and typical Alzheimer's disease for each oculomotor metric, choosing the cut-off that maximized the percentage of patients correctly classified (accuracy).
In this study, we show that phosphatase PRL-3 is an independent marker of aggressiveness and distant dissemination of locally advanced CRC and a useful tool to classify the accuracy of stage III CRC regarding the risk of distant relapse.
When the number of training samples is more than 500, KMRBF-BP can get a higher classifying accuracy than KM-RBF.
These results show that the hybrid RBF-BP network architecture is effective, which can improve the classifying accuracy and reduce the dependence on the original sample space mapping.
