Description Usage Arguments Details Value Author(s) See Also Examples

Wrapper for performing feature ranking method on multiple subsets of the original
data. At each iteration, only the training samples defined in `tr.idx`

(or optionally `pars`

only) are used to rank the variables.
Features rank, order and saliency indicators calculated on the whole data are
also given in the output. As for `accest`

this function allows the use of multiple processors
as long as the cluster has been set up with the snow package. Data input can be
in the form of `data`

matrix + `class`

vector, following the classic formula type or
derived from `dat.sel1`

.

1 2 3 4 5 6 7 8 9 10 | ```
feat.rank.re(...)
## Default S3 method:
feat.rank.re(x,y,method,pars = valipars(),tr.idx=NULL,clmpi=NULL, seed=NULL, ...)
## S3 method for class 'formula'
feat.rank.re(formula, data = NULL, ...)
## S3 method for class 'dlist'
feat.rank.re(dlist, method, pars = NULL, tr.idx = NULL, ...)
``` |

`formula` |
A formula of the form |

`x` |
A matrix or data frame containing the explanatory variables. |

`dlist` |
A matrix or data frame containing the explanatory variables if no formula is given as the principal argument. |

`data` |
Data frame from which variables specified in |

`y` |
A factor specifying the class for each observation. |

`method` |
Feature ranking method to be used.
See |

`pars` |
A list of resampling scheme or validation method such as |

`tr.idx` |
User defined index of training samples of type |

`clmpi` |
snow cluster information |

`seed` |
Seed. |

`...` |
Additional parameters to be passed to |

The structure of the `feat.rank.re`

object is as follows:

- method
Feature ranking method used.

- fs.rank
A vector of final feature ranking scores.

- fs.order
A vector of final feature order from best to worst.

- fs.stats
A vector of means of statistics or measurements in all computation.

- rank.list
Feature rank list of all computation.

- order.list
Feature order list of all computation.

- pars
Resampling parameters.

- tr.idx
Index of training samples.

- pars.min
Condensed form of the resampling strategy for output purposes.

- cl.task
Condensed form of the classification task.

- all
Feature ranking object originated from the overall dataset.

`feat.rank.re`

object.

David Enot [email protected]

`valipars`

, `ftrank.agg`

, `fs.techniques`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
## load abr1
data(abr1)
y <- factor(abr1$fact$class)
x <- preproc(abr1$pos , y=y, method=c("log10","TICnorm"),add=1)[,110:500]
## Select classes 1 and 2
pars <- valipars(sampling="boot",niter=2,nreps=5)
dat <- dat.sel1(x, y, pwise=c("1","2"),mclass=NULL,pars=pars)
## multiple rankings using AUC
z <- feat.rank.re(dat[[1]],method="fs.auc")
## print content of z
names(z)
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.