Answer: question regarding .632plus error rate estimator in ipred package
I think that there is some confusion here:
> there is .632plus estimator, but seems that this estimator
> does not have feature selection built in
The 632 estimator is a method of evaluating model performance form a
training set (using the bootstrap). It knows nothing about the model.
Feature selection methods happen either as wrappers around the model
for some models, as built-in qualities of the model (e.g. rpart or
nearest shrunken centroids). Functionally, feature selection has
to do with resampling estimators of model quality.
In practice, it is more complicated. You should take great care when
estimating performance on a training set when you are using a feature
selection algorithm. You should read:
and the references therein.
[mailto:bioconductor-bounces at stat.math.ethz.ch] On Behalf Of James
Sent: Tuesday, October 30, 2007 5:29 PM
Subject: [BioC] question regarding .632plus error rate estimator in
Sorry to bother those who are not interested. In the ipred package,
there is .632plus estimator, but seems that this estimator does not
feature selection built in. If that is the case, I am wondering how
can be applied to microarray, since feature selection is a must for
microarray. If feature selection is done on the entire dataset and
perform .632plus later, there will be some bias with the leave-one-out
bootstrap part. I think other estimators should be the same in the
that it is done on the dataset without performing feature selection.
what I understand correct or not?
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