llama: Leveraging Learning to Automatically Manage Algorithms

Provides functionality to train and evaluate algorithm selection models for portfolios.

Install the latest version of this package by entering the following in R:
install.packages("llama")
AuthorLars Kotthoff [aut,cre], Bernd Bischl [aut], Barry Hurley [ctb], Talal Rahwan [ctb]
Date of publication2015-12-05 15:28:10
MaintainerLars Kotthoff <larsko@cs.ubc.ca>
LicenseBSD_3_clause + file LICENSE
Version0.9.1
https://bitbucket.org/lkotthoff/llama

View on CRAN

Functions

bsFolds Man page
classify Man page
classifyPairs Man page
cluster Man page
contributions Man page
cvFolds Man page
imputeCensored Man page
input Man page
llama Man page
llama-package Man page
makeRLearner.classif.constant Man page
misclassificationPenalties Man page
normalize Man page
parscores Man page
perfScatterPlot Man page
predictLearner.classif.constant Man page
predTable Man page
print.llama.data Man page
print.llama.model Man page
regression Man page
regressionPairs Man page
satsolvers Man page
singleBest Man page
singleBestByCount Man page
singleBestByPar Man page
singleBestBySuccesses Man page
successes Man page
trainLearner.classif.constant Man page
trainTest Man page
tuneModel Man page
vbs Man page

Files

inst
inst/java
inst/java/ShapleyValue.jar
inst/manual
inst/manual/llama.pdf
tests
tests/run-all.R
tests/testthat
tests/testthat/test.misc.R tests/testthat/test.parscores.R tests/testthat/helper_mockLearners.R tests/testthat/test.satsolvers.R tests/testthat/test.cluster.R tests/testthat/test.classify.R tests/testthat/test.trainTest.R tests/testthat/test.regression.R tests/testthat/test.classifyPairs.R tests/testthat/test.misclassificationPenalties.R tests/testthat/test.successes.R tests/testthat/test.input.R tests/testthat/test.cvFolds.R tests/testthat/test.tune.R tests/testthat/test.bsFolds.R tests/testthat/helper_testData.R tests/testthat/test.imputeCensored.R tests/testthat/test.regressionPairs.R tests/testthat/test.analysis.R tests/testthat/test.normalize.R
NAMESPACE
NEWS
data
data/satsolvers.rda
R
R/regressionPairs.R R/misclassificationPenalties.R R/helpers.R R/regression.R R/imputeCensored.R R/trainTest.R R/plot.R R/bsFolds.R R/analysis.R R/parscores.R R/cvFolds.R R/cluster.R R/input.R R/normalize.R R/misc.R R/successes.R R/classify.R R/tune.R R/zzz.R R/classifyPairs.R
MD5
java
java/shapleyComputation
java/shapleyComputation/ShapleyComputation.class
java/shapleyComputation/Combinations.java
java/shapleyComputation/Combinations.class
java/shapleyComputation/CoalitionValueCalculator.class
java/shapleyComputation/ShapleyComputation.java
java/shapleyComputation/CoalitionValueCalculator.java
DESCRIPTION
man
man/tune.Rd man/satsolvers.Rd man/classifyPairs.Rd man/input.Rd man/cvFolds.Rd man/cluster.Rd man/classify.Rd man/analysis.Rd man/imputeCensored.Rd man/llama-package.Rd man/successes.Rd man/regression.Rd man/bsFolds.Rd man/normalize.Rd man/parscores.Rd man/trainTest.Rd man/regressionPairs.Rd man/plot.Rd man/helpers.Rd man/misc.Rd man/misclassificationPenalties.Rd
LICENSE

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.