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Last update: February 19, 2014
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Bounded Rank Fitness Function
The Bounded Rank fitness function is based on the rank measure.
It allows you to set boundaries for the model output,
which the learning algorithm will try to approach.
In addition, it can be combined
with a cost matrix in order to impose specific constraints on the
solutions.
In addition, by choosing different
rounding thresholds,
different fitness functions can be created to explore different solution spaces.
The evolvable rounding thresholds include the ROC threshold, the logistic, class proportions, large margin, average, RMS, interdecile mean,
interquartile mean, midrange, midhinge, and trimean threshold. There are also
two kinds of fixed thresholds: the rounding threshold of the active model and
user defined thresholds.
See Also:
Related Tutorials:
Related Videos:
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