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The developed estimation models are evaluated using different evaluation metrics.
Changes are evaluated using population statistics, which are useful in detecting subtle changes across two populations.
The algorithms are evaluated using an FPGA.
These parameters are evaluated using empirical formulae.
Experimental results are evaluated using standard parameters: precision and recall.
Generally, the solutions available are evaluated using fitness function.
These probabilities are evaluated using all available training data.
All predictions are evaluated using the cost function g2.
Presently, serial CA125 levels in patients are evaluated using immunoassays.
Competing protection options are evaluated using a survivability metric.
These coupling methods are evaluated using picture frame test simulations.
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