RFQueryTurbineModel: Use a random forest model to predict response to forcing...
In AndyClifton/PowerPerformance: Package to analyze wind resource and wind turbine data (developer test version)
Description
Usage
Arguments
Value
See Also
Description
RFQueryTurbineModel uses a trained random forest model to estimate the
response to a set of forcing conditions (predictors).
Usage
1
RFQueryTurbineModel(predictors, model)
Arguments
predictors
a data.frame of predictors corresponding to the data.frame
used to train the model
model
a model object that was trained using predictors with the same names
Value
mean and standard deviation of the values from the model
See Also
Other Random forest methods: RFCheckVarImp;
RFChecknTrees;
RFTrainTestTurbineModel;
RFTrainTurbineModel
AndyClifton/PowerPerformance documentation built on May 5, 2019, 6 a.m.
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Description Usage Arguments Value See Also
Description
RFQueryTurbineModel uses a trained random forest model to estimate the
response to a set of forcing conditions (predictors).
Usage
1 | RFQueryTurbineModel(predictors, model)
|
Arguments
predictors |
a data.frame of predictors corresponding to the data.frame used to train the model |
model |
a model object that was trained using predictors with the same names |
Value
mean and standard deviation of the values from the model
See Also
Other Random forest methods: RFCheckVarImp;
RFChecknTrees;
RFTrainTestTurbineModel;
RFTrainTurbineModel
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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