| Name : R-adabag
| |
| Version : 4.3
| Vendor : obs://build_opensuse_org/devel:languages:R
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| Release : lp153.1.5
| Date : 2024-06-14 11:37:08
|
| Group : Development/Libraries/Other
| Source RPM : R-adabag-4.3-lp153.1.5.src.rpm
|
| Size : 0.12 MB
| |
| Packager : (none)
| |
| Summary : Applies Multiclass AdaBoost.M1, SAMME and Bagging
|
Description :
It implements Freund and Schapire\'s Adaboost.M1 algorithm and Breiman\'s
Bagging algorithm using classification trees as individual classifiers.
Once these classifiers have been trained, they can be used to predict
on new data. Also, cross validation estimation of the error can be
done. Since version 2.0 the function margins() is available to
calculate the margins for these classifiers. Also a higher flexibility
is achieved giving access to the rpart.control() argument of \'rpart\'.
Four important new features were introduced on version 3.0,
AdaBoost-SAMME (Zhu et al., 2009) is implemented and a new function
errorevol() shows the error of the ensembles as a function of the
number of iterations. In addition, the ensembles can be pruned using
the option \'newmfinal\' in the predict.bagging() and predict.boosting()
functions and the posterior probability of each class for observations
can be obtained. Version 3.1 modifies the relative importance measure
to take into account the gain of the Gini index given by a variable in
each tree and the weights of these trees. Version 4.0 includes the
margin-based ordered aggregation for Bagging pruning (Guo and Boukir,
2013) and a function to auto prune the \'rpart\' tree. Moreover, three
new plots are also available importanceplot(), plot.errorevol() and
plot.margins(). Version 4.1 allows to predict on unlabeled data.
Version 4.2 includes the parallel computation option for some of the
functions.
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RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
