ClassifierBuild {MCRestimate} | R Documentation |
Building a classifier as a combination of preprocessing and
classification method
Description
Usage
ClassifierBuild(eset,
class.column,
reference.class=NULL,
classification.fun,
variableSel.fun ="identity",
cluster.fun ="identity",
poss.parameters=list(),
cross.inner=10,
rand=123,
information=TRUE,
thePreprocessingMethods=c(variableSel.fun,cluster.fun))
Arguments
eset |
an object of class exprSet or exprSetRG |
class.column |
a number or a character string which indicated the column of the expression set's phenodata containing the class label |
reference.class |
a character string with the name of one class - if specified the class will form the first class and all the other classes will form the second class |
classification.fun |
a character string which names the function that should be used for the classification |
variableSel.fun |
character string which names the function that should be used for variable selection |
cluster.fun |
character string which names the function that should be used for clustering the variables |
thePreprocessingMethods |
vector of character with the names of all preprocessing functions- can be used instead of 'variableSel.fun' and 'cluster.fun' - see details |
poss.parameters |
a list of possible values for the parameter of the classification method |
cross.inner |
integer - the number of nearly equal sized parts the train set should be divided into |
rand |
integer - the random number generator will be put in a reproducible state |
information |
information - should classificator specific data be given(depends on the wrapper for the classification method) |
Value
a list
with the following arguments:
classifier.for.matrix |
|
classifier.for.exprSet |
|
parameter |
a list consisting of the estimated 'best' parameter
for each cross-validation part |
class.method |
string which names the function used for the
classification |
thePreprocessingMethods |
character string - name of the
preprocessing functions that have been used |
cross.inner |
number of blocks for a the inner cross-validation |
information |
classificator specific data |
Author(s)
Markus Ruschhaupt mailto:m.ruschhaupt@dkfz.de
Examples
## please have a look at the vignette of this package
[Package
MCRestimate version 1.4.0
Index]