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Last update: February 19, 2014
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Bounded Trends R2 Fitness Function
The Bounded Trends R2 fitness function
is a multi-objective function that explores the idea of trends
and attributes rewards or punishments when a model hits or not on the trend.
It also combines the up/down hits with the
Root Relative Squared Error (RRSE).
The RRSE 2 component is implemented so that you can choose different
simple models besides the usual target average.
Moreover, the RRSE 2 differs from the common RRSE in the evaluation of the denominator term,
where instead of using the target output to calculate the difference between
the target and the simple model, the model output is used instead, resulting in a more dynamic,
forever adapting solution space.
Furthermore, it allows you to set boundaries for the model output,
which the learning algorithms will try to approach.
The Bounded Trends R2 fitness function is particularly useful for time series data.
See Also:
Related Tutorials:
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