The main goal of this function is to facilitate the generation of
different variants of a learning system. The idea is to be able to
supply several possible values for a set of parameters of the learner,
and then have the function to return a set of
each consisting of one of the different possible combinations of the
variants. This function finds its use in the context of experimental
comparisons among learning systems, where we may actually be interested
in comparing different parameter settings for each of them.
This is the string representing the name of the function of the base learner from which variants should be generated.
By default the names given to each variant will be formed by concatenating the base name of the learner with the terminations: ".v1", ".v2", and so on. This parameter allows you to supply a different base name.
This is a vector of parameter names (defaults to
The function then accepts any number of named arguments, each with a set of values. These named arguments are supposed to be the names of arguments of the base learner, while the sets of values are the alternatives that you want to consider in the variants generation (see examples below).
The result of this function is a list of
learner objects. Each
of these objects represents one of the parameter variants of the
learner you have supplied.
Luis Torgo [email protected]
Torgo, L. (2010) Data Mining using R: learning with case studies, CRC Press (ISBN: 9781439810187).
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