llama v0.9.2

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Leveraging Learning to Automatically Manage Algorithms

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

Functions in llama

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

Type Package
Date 2018-07-11
License BSD_3_clause + file LICENSE
URL https://bitbucket.org/lkotthoff/llama
NeedsCompilation no
Packaged 2018-07-11 10:43:46 UTC; larsko
Repository CRAN
Date/Publication 2018-07-11 14:30:03 UTC

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