Description Format Usage Arguments Details Fields Methods Examples
BaselearnerCustomCpp creates a custom base-learner factory by
setting custom C++ functions. This factory object can be registered
within a base-learner list and then used for training.
S4 object.
1 2 | BaselearnerCustomCpp$new(data_source, data_target, instantiate_data_ptr,
train_ptr, predict_ptr)
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data_source [Data Object]Data object which contains the source data.
data_target [Data Object]Data object which gets the transformed source data.
instantiate_data_ptr [externalptr]External pointer to the C++ instantiate data function.
train_ptr [externalptr]External pointer to the C++ train function.
predict_ptr [externalptr]External pointer to the C++ predict function.
For an example see the extending compboost vignette or the function
getCustomCppExample.
This class is a wrapper around the pure C++ implementation. To see
the functionality of the C++ class visit
https://schalkdaniel.github.io/compboost/cpp_man/html/classblearnerfactory_1_1_custom_cpp_blearner_factory.html.
This class doesn't contain public fields.
getData()Get the data matrix of the target data which is used for modeling.
transformData(X)Transform a data matrix as defined within the factory. The argument has to be a matrix with one column.
summarizeFactory()Summarize the base-learner factory object.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | # Sample data:
data.mat = cbind(1, 1:10)
y = 2 + 3 * 1:10
# Create new data object:
data.source = InMemoryData$new(data.mat, "my.data.name")
data.target = InMemoryData$new()
# Source the external pointer exposed by using XPtr:
Rcpp::sourceCpp(code = getCustomCppExample(silent = TRUE))
# Create new linear base-learner:
custom.cpp.factory = BaselearnerCustomCpp$new(data.source, data.target,
dataFunSetter(), trainFunSetter(), predictFunSetter())
# Get the transformed data:
custom.cpp.factory$getData()
# Summarize factory:
custom.cpp.factory$summarizeFactory()
# Transform data manually:
custom.cpp.factory$transformData(data.mat)
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