Package: aslib 0.1.3

Lars Kotthoff

aslib: Interface to the Algorithm Selection Benchmark Library

Provides an interface to the algorithm selection benchmark library at <https://www.coseal.net/aslib/> and the 'LLAMA' package (<https://cran.r-project.org/package=llama>) for building algorithm selection models; see Bischl et al. (2016) <doi:10.1016/j.artint.2016.04.003>.

Authors:Bernd Bischl [aut], Lars Kotthoff [aut, cre], Pascal Kerschke [ctb, aut], Damir Pulatov [ctb, aut]

aslib_0.1.3.tar.gz
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aslib_0.1.3.tgz(r-4.6-any)aslib_0.1.3.tgz(r-4.5-any)
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manual.pdf |manual.html✨
card.svg |card.png
aslib/json (API)
NEWS

# Install 'aslib' in R:

install.packages('aslib', repos = c('https://coseal.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/coseal/aslib-r/issues

Uses libs:

openjdk– OpenJDK Java runtime, using Hotspot JIT

On CRAN:

openjdk

4.77 score 8 stars 37 scripts 278 downloads 32 exports 52 dependencies

Last updated from:bf25e92ec6. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	201
source / vignettes	OK	194
linux-release-x86_64	OK	185
macos-release-arm64	OK	192
macos-oldrel-arm64	OK	270
windows-devel	OK	151
windows-release	OK	157
windows-oldrel	OK	135
wasm-release	OK	145

Exports:checkDuplicatedInstances convertAlgoPerfToWideFormat convertToLlama convertToLlamaCVFolds createCVSplits findDominatedAlgos fixFeckingPresolve getAlgorithmNames getCosealASScenario getCostsAndPresolvedStatus getDefaultFeatureStepNames getFeatureNames getFeatureStepNames getInstanceNames getNumberOfCVFolds getNumberOfCVReps getProvidedFeatures getSummedFeatureCosts imputeAlgoPerf parseASScenario plotAlgoCorMatrix plotAlgoPerfBoxplots plotAlgoPerfCDFs plotAlgoPerfDensities plotAlgoPerfScatterMatrix runLlamaModels summarizeAlgoPerf summarizeAlgoRunstatus summarizeFeatureSteps summarizeFeatureValues summarizeLlamaExps writeASScenario

Dependencies:backports base64url batchtools BBmisc brew checkmate cli corrplot cpp11 crayon data.table digest farver fastmatch fs ggplot2 glue gtable hms isoband labeling lattice lifecycle llama magrittr Matrix mlr parallelMap ParamHelpers pkgconfig plyr prettyunits progress R6 rappdirs RColorBrewer Rcpp reshape2 rJava rlang RWeka RWekajars S7 scales stringi stringr survival vctrs viridisLite withr XML yaml

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
S3 class for ASScenarioDesc.	ASScenarioDesc
Checks the feature data set for duplicated instances.	checkDuplicatedInstances
Converts 'algo.runs' object of a scenario to wide format.	convertAlgoPerfToWideFormat
Convert an ASScenario scenario object to a llama data object.	convertToLlama
Convert an ASScenario scenario object to a llama data object with cross-validation folds.	convertToLlamaCVFolds
Create cross-validation splits for a scenario.	createCVSplits
Creates a table that shows the dominance of one algorithm over another one.	findDominatedAlgos
Bakes presolving stuff into a LLAMA data frame.	fixFeckingPresolve
Returns algorithm names of scenario.	getAlgorithmNames
Retrieves a scenario from the Coseal Github repository and parses into an S3 object.	getCosealASScenario
Return whether an instance was presolved and which step did it.	getCostsAndPresolvedStatus
Returns the default feature step names of scenario.	getDefaultFeatureStepNames
Returns feature names of scenario.	getFeatureNames
Returns feature step names of scenario.	getFeatureStepNames
Returns instance names of scenario.	getInstanceNames
Returns number of CV folds.	getNumberOfCVFolds
Returns number of CV repetitions.	getNumberOfCVReps
Return features that are useable for a given set of feature steps.	getProvidedFeatures
Returns feature costs of scenario, summed over all instances.	getSummedFeatureCosts
Imputes algorithm performance for runs which have NA performance values.	imputeAlgoPerf
Parses the data files of an algorithm selection scenario into an S3 object.	ASScenario parseASScenario
Plots the correlation matrix of the algorithms.	plotAlgoCorMatrix
EDA plots for performance values of algorithms across all instances.	plotAlgoPerf plotAlgoPerfBoxplots plotAlgoPerfCDFs plotAlgoPerfDensities plotAlgoPerfScatterMatrix
Creates a registry which can be used for running several Llama models on a cluster.	runLlamaModels
Creates summary data.frame for algorithm performance values across all instances.	summarizeAlgoPerf
Creates summary data.frame for algorithm runstatus across all instances.	summarizeAlgoRunstatus
Creates a data.frame that summarizes the feature steps.	summarizeFeatureSteps
Creates summary data.frame for feature values across all instances.	summarizeFeatureValues
Creates summary data.table for runLlamaModel experiments.	summarizeLlamaExps
Writes an algorithm selection scenario to a directory.	writeASScenario