(a) Binary signal reconstruction error and (b) correct classification ratio.
We also include in Table 1 the correct classification ratio.
(a) Gaussian signal reconstruction error and (b) Correct classification ratio.
Hence, the target of classification system design is gradually shifting from seeking a system with the maximum classification accuracy to obtain a system with the maximum AUC/MAUC.
For parameter optimization of SVM classifier, f ( x → ) could be minimum classification error or maximum classification accuracy.
The outcome confirms that the maximum classification accuracy (99.28%) is achieved for this study.
The iteration in which maximum classification performance occurs is considered as optimum iteration.
In contrast to the approach used in previous work, these patterns contain application-specific parameters, such as peak-to-noise ratio (PNR), average amplitude ratio (AvAR) and maximum amplitude ratio (MAR), in order to improve classification efficiency.
Introduce a maximum pay ratio of 10 1 between the best paid and worst paid in any organisation.
maximum likelihood ratio test.
