llama: Leveraging Learning to Automatically Manage Algorithms

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

Author
Lars Kotthoff [aut,cre], Bernd Bischl [aut], Barry Hurley [ctb], Talal Rahwan [ctb]
Date of publication
2015-12-05 15:28:10
Maintainer
Lars Kotthoff <larsko@cs.ubc.ca>
License
BSD_3_clause + file LICENSE
Version
0.9.1
URLs

View on CRAN

Man pages

analysis
Analysis functions
bsFolds
Bootstrapping folds
classify
Classification model
classifyPairs
Classification model for pairs of algorithms
cluster
Cluster model
cvFolds
Cross-validation folds
helpers
Helpers
imputeCensored
Impute censored values
input
Read data
llama-package
Leveraging Learning to Automatically Manage Algorithms
misc
Convenience functions
misclassificationPenalties
Misclassification penalty
normalize
Normalize features
parscores
Penalized average runtime score
plot
Plot convenience functions to visualise selectors
regression
Regression model
regressionPairs
Regression model for pairs of algorithms
satsolvers
Example data for Leveraging Learning to Automatically Manage...
successes
Success
trainTest
Train / test split
tune
Tune the hyperparameters of the machine learning algorithm...

Files in this package

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