§ 1005.45 Market administrator's reports and announcements concerning classification.
From a statistical point of view, as reviewed by Simon [14], this type of prediction is a complicated problem and many factors, such as gene selection rules, sample resubstitution approaches, sample size concerns, and classification methods are involved.
We examine the accuracy and robustness of our technique by comparing the classification accuracy of our technique, a maximum entropy-based aggregation technique, and four classification methods on a real-world, two-group data-set concerned with bank failure prediction.
The new spectrum regulation policies for dynamic spectrum access, especially those concerning the use of the white spaces in the Digital Terrestrial Television (DTT) bands, arise the need for fast and reliable signal identification and classification methods.
Disorder/order classification methods generally perform poorly on the disorder design task65.
The vast majority of these studies have focused on the development of disorder/order classification methods.
Comparison of viral clusters with other classification methods (phage proteomic tree and percentage of shared genes).
Spectral-based classification methods have gained increasing attention in hyperspectral imagery classification.
Current drought classification methods ignore modeling uncertainties and provide discrete drought classification.
Discussions on defect classification methods.
Let us first introduce traditional classification methods.
