| default_fs_fun {RAFS} | R Documentation |
Default (example) feature selection function for RAFS
Description
See run_rafs for how it is used. Only the train portion of the
dataset is to be fed into this function.
Usage
default_fs_fun(train_data, train_decision, seed)
Arguments
train_data |
input data where columns are variables and rows are observations (all numeric) |
train_decision |
decision variable as a binary sequence of length equal to number of observations |
seed |
a numerical seed |
Details
The function MUST use this train_data and MAY ignore
the train_decision.
If the function depends on randomness, it MUST use the seed parameter to seed the PRNG.
The function needs to return a list with at least two elements:
rel_vars and rel_vars_rank, which are vectors and contain,
respectively, the indices of variables considered relevant and the rank
for each relevant variable. The function MAY return a list with more elements.
Other examples of sensible functions are included in the tests of this package.
Value
A list with at least two fields:
rel_vars and rel_vars_rank, which are vectors and contain,
respectively, the indices of variables considered relevant and the rank
for each relevant variable.