Displaying 9 results from an estimated 9 matches for "logitboost".
2008 Aug 25
3
name conflicts
Everyone,
I've got code in my package that uses LogitBoost from the caTools
package. caTools does not have a namespace.
My package also uses loads RWeka, which has a namespace, and also has
a function called LogitBoost.
After loading both packages, how can I be specific about running the
version from caTools (since caTools:::LogitBoost won't work)?...
2009 Sep 15
1
Boost in R
Hello,
does any one know how to interpret this output in R?
> Classification with logitboost
> fit <- logitboost(xlearn, ylearn, xtest, presel=50, mfinal=20)
> summarize(fit, ytest)
Minimal mcr: 0 achieved after 6 boosting step(s)
Fixed mcr: 0 achieved after 20 boosting step(s)
What is "mcr" mean?
Thanks
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2009 Mar 28
2
Output an RWeka model via sink
When I sink the output of an RWeka model to a text file, the output file appears empty:
library(RWeka)
model = LogitBoost(Species~.,data=iris)
print(model)
sink("output.txt")
print(model)
#file output.txt is created, but it is blank
sink()
Am I doing anything wrong?
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2002 Jun 23
2
AdaBoost for R
I'm going to implement AdaBoost algorithm in R. Just wanted to ensure
that there is no implementation of any boosting algorithm in R... don't
want
to reinvent the wheel...
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2005 Jul 12
1
SOS Boosting
Hi,
I am trying to implement the Adaboost.M1. algorithm as described in
"The Elements of Statistical Learning" p.301
I don't use Dtettling 's library "boost" because :
- I don't understande the difference beetween Logitboost and L2boost
- I 'd like to use larger trees than stumps.
By using option weights set to (1/n, 1/n, ..., 1/n) in rpart or tree
function, the tree obtained is trivial (just root, no split) whereas
without weight or for each weight >1,trees are just fine.
So here is my question : how are we...
2012 Jan 04
3
informal conventions/checklist for new predictive modeling packages
...require a test set when model building.
(7) Control all written output during model-building time with a
verbose option. Resampling can make a mess out of things if
output/logging is always exposed.
(8) Please use RSiteSearch to avoid name collisions between packages
(eg. gam(), splsda(), roc(), LogitBoost()). Also search Bioconductor.
(9) Allow the predict function to generate results from many different
sub-models simultaneously. For example, pls() can return predictions
across many values of ncomp. enet(), cubist(), blackboost() are other
examples.
corollary (9a): [OCD] ensure the same object ty...
2008 Sep 06
0
New caret packages
...s now hosted on R-Forge. The homepage is
http://caret.r-forge.r-project.org/
The package currently includes model tuning/resampling for the following
models: lm, single trees (C4.5, rpart, ctree, logistic model trees), mars
(via earth), boosted models (ada, gbm, blackboost, glmboost, gamboost,
logitboost), bagged models (trees, earth, fda), randomforests (randomforest
and cforest), rule-based models (Ripper and M5 prime), discriminant models
(lda, fda, rda, ssda, slda), kernel methods (lssvm, ksvm, rvm, gausspr),
nnet, nnet with initial pca step, multinom, pls, plsda, gpls, nearest
shrunken centroi...
2008 Sep 06
0
New caret packages
...s now hosted on R-Forge. The homepage is
http://caret.r-forge.r-project.org/
The package currently includes model tuning/resampling for the following
models: lm, single trees (C4.5, rpart, ctree, logistic model trees), mars
(via earth), boosted models (ada, gbm, blackboost, glmboost, gamboost,
logitboost), bagged models (trees, earth, fda), randomforests (randomforest
and cforest), rule-based models (Ripper and M5 prime), discriminant models
(lda, fda, rda, ssda, slda), kernel methods (lssvm, ksvm, rvm, gausspr),
nnet, nnet with initial pca step, multinom, pls, plsda, gpls, nearest
shrunken centroi...
2011 Mar 30
0
RWeka - adding weights to a dataset
Hello, I was wondering what would be the easiest way to append weights to a dataset in RWeka.
Ideally, I'd like to have something like:
m <- LogitBoost(Species ~ ., data=iris, weights = myweights)
But that, as far as I understand, it is not implemented and I'd need to use a workaround.
I know that when programming Weka in Java it is possible to assign weights to instances using the setWeight, but I don't know exactly what would be the...