The overall problem is to find these parameters such that perfect classification is achieved.
An eAUC of 1.0 represents perfect classification with no false positives or negatives.
It's going to be measured with area under the ROC curve. 1 is perfect classification and 0.5 is chance.
The results obtained for (a) were a perfect classification rate using either one of the modeling approaches.
Although a perfect classification lies at present beyond scholars' grasp, certain criteria, both positive and negative in nature, may be suggested for building and judging classifications.
The area under the curve indicates the ability of the classifier to detect deviation from baseline (i.e., detection probability): an area of 1.0 indicates perfect classification; an area of 0.5 indicates chance discrimination by the classifier.
Expanded bed adsorption (EBA) is a special chromatography technique with perfect classification of adsorbent particles in the column, thus the performance of protein adsorption in expanded beds is particular, obviously nonuniform and complex along the column.
Perfect classification is achieved when the length of the segment is 6.22 sec.
The perfect classification represents when the physician agrees with the epilepsy risk level.
SVD optimization has the highest value of perfect classification rate of 96.58% with zero false alarms.
By experiment, it is verified that the GVCA method has a perfect classification performance with a rapid rate of convergence.
