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To evaluate such unbalanced data, evaluation measure such as overall accuracy, the Mathews correlation coefficient and F-measure is not adequate.
There has been some work on evaluating these systems with the efficiency as the main evaluation measure.
The evaluation measure most used in practice is the accuracy rate which evaluates effectiveness of the classifier by its percentage of correct prediction.
Evaluating evaluation measure stability.
In this section, instead of using the number of correctly classified test documents (or, equivalently, the error rate on test documents) as evaluation measure, we adopt an evaluation measure that addresses the inherent uncertainty of labeling.
The choice of an evaluation measure should be driven primarily by the goals of the study.
It is known that dependency is an important feature evaluation measure based on rough set theory.
A prototype of the framework is built using Web Services and a complexity evaluation measure is presented.
One such evaluation measure is the depletion number, which relates the exergy destruction and exergy input for a system.
In this paper, a new and combined evaluation measure based on genetic programming (GP) has been sought.
F1Score is a performance evaluation measure.
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