FunctionalModel.fit.de: Use Differential Evolution to Optimize the Parameters
In thomasWeise/regressoR.functional: An R Package for Fitting Functional Models to 2-Dimensional Data
Description
Usage
Arguments
Value
Description
Apply the Differential Evolution (DE) algorithm to fit a
functional model.
Usage
1
FunctionalModel.fit.de(metric, model, par = NULL, q = 0.75)
Arguments
metric
an instance of
regressoR.quality::RegressionQualityMetric
model
an instance of FunctionalModel
par
the initial starting point
q
the effort to spent in learning, a value between 0 (min) and 1
(max). Higher values may lead to much more computational time, lower values
to potentially lower result quality.
Value
On success, an instance of FittedFunctionalModel.
NULL on failure.
thomasWeise/regressoR.functional documentation built on May 10, 2019, 10:24 a.m.
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Description Usage Arguments Value
Description
Apply the Differential Evolution (DE) algorithm to fit a functional model.
Usage
1 | FunctionalModel.fit.de(metric, model, par = NULL, q = 0.75)
|
Arguments
metric |
an instance of
|
model |
an instance of |
par |
the initial starting point |
q |
the effort to spent in learning, a value between 0 (min) and 1 (max). Higher values may lead to much more computational time, lower values to potentially lower result quality. |
Value
On success, an instance of FittedFunctionalModel.
NULL on failure.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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