sampling_sequence applies a sequence of sampling algorithms to an
input data set.
A data frame containing the predictors and the outcome.
Restrictions about the input data depend on the individual sampling
algorithms being used. In any case, the outcome must be both a binary
valued factor and the last column of
A vector containing the names of the sampling algorithms to be chained either as strings or the functions' objects themselves.
A list of lists where each individual list contains the
parameters to be used by the respective sampling algorithm in
A named vector identifying the majority and the minority classes. The names must be "Majority" and "Minority". This argument is only useful if the function is called inside another sampling function.
sampling_sequence has two main arguments:
algorithms is a vector containing the names of
the sampling functions to be applied in sequence (either as strings or
the functions' objects themselves).
parameters is a list of lists,
where each individual list contains the parameters to be used by the
respective sampling function in
A data frame containing the result of a chain of sampling algorithms applied to the input data set.
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