sbfControl

0th

Percentile

Control Object for Selection By Filtering (SBF)

Controls the execution of models with simple filters for feature selection

Keywords
utilities
Usage
sbfControl(functions = NULL, 
           method = "boot", 
           saveDetails = FALSE, 
           number = ifelse(method %in% c("cv", "repeatedcv"), 10, 25),
           repeats = ifelse(method %in% c("cv", "repeatedcv"), 1, number),
           verbose = FALSE, 
           returnResamp = "all", 
           p = 0.75, 
           index = NULL, 
           timingSamps = 0)
Details

Simple filter-based feature selection requires function to be specified for some operations.

The fit function builds the model based on the current data set. The arguments for the function must be:

  • x
{ the current training set of predictor data with the appropriate subset of variables (i.e. after filtering)} y{ the current outcome data (either a numeric or factor vector)} ...{ optional arguments to pass to the fit function in the call to sbf}

Value

  • a list that echos the specified arguments

code

nbSBF

itemize

  • score

item

  • x
  • y
  • x
  • y

See Also

sbf, caretSBF, lmSBF, rfSBF, treebagSBF, ldaSBF and nbSBF

Aliases
Documentation reproduced from package caret, version 5.07-001, License: GPL-2

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