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performanceEstimation
View on CRAN: Click
here
Download and install performanceEstimation package within the R console
Install from CRAN:
install.packages("performanceEstimation")
Install from Github:
library("remotes")
install_github("cran/performanceEstimation")
Install by package version:
library("remotes")
install_version("performanceEstimation", "1.1.0")
Attach the package and use:
library("performanceEstimation")
Maintained by
Luis Torgo
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.performanceEstimation . https://github.com/ltorgo/performanceEstimation/issues . https://github.com/ltorgo/performanceEstimation . performanceEstimation citation info . performanceEstimation results . performanceEstimation.pdf . performanceEstimation_1.1.0.tar.gz . performanceEstimation_1.1.0.zip . performanceEstimation_1.1.0.zip . performanceEstimation_1.1.0.zip . performanceEstimation_1.1.0.tgz . performanceEstimation_1.1.0.tgz . performanceEstimation_1.1.0.tgz . performanceEstimation_1.1.0.tgz . performanceEstimation_1.1.0.tgz . performanceEstimation_1.1.0.tgz . performanceEstimation archive . https://CRAN.R-project.org/package=performanceEstimation .
First Published: 2013-12-29
Latest Update: 2016-10-13
Description:
An infra-structure for estimating the predictive performance of
predictive models. In this context, it can also be used to compare and/or select
among different alternative ways of solving one or more predictive tasks. The
main goal of the package is to provide a generic infra-structure to estimate
the values of different metrics of predictive performance using different
estimation procedures. These estimation tasks can be applied to any solutions
(workflows) to the predictive tasks. The package provides easy to use standard
workflows that allow the usage of any available R modeling algorithm together
with some pre-defined data pre-processing steps and also prediction post-
processing methods. It also provides means for addressing issues related with
the statistical significance of the observed differences.
How to cite:
Luis Torgo (2013). performanceEstimation: An Infra-Structure for Performance Estimation of Predictive Models. R package version 1.1.0, https://cran.r-project.org/web/packages/performanceEstimation. Accessed 01 Apr. 2025.
Previous versions and publish date:
Other packages that cited performanceEstimation R package
View performanceEstimation citation profile
Other R packages that performanceEstimation depends,
imports, suggests or enhances
Complete documentation for performanceEstimation
Functions, R codes and Examples using
the performanceEstimation R package
Some associated functions: Bootstrap-class . CDdiagram.BD . CDdiagram.Nemenyi . CV-class . ComparisonResults-class . EstCommon-class . EstimationMethod-class . EstimationResults-class . EstimationTask-class . Holdout-class . LOOCV-class . MonteCarlo-class . PredTask-class . Workflow-class . bootEstimates . classificationMetrics . cvEstimates . estimationSummary . getIterationsInfo . getIterationsPreds . getScores . getWorkflow . hldEstimates . is.classification . is.regression . knnImp . loocvEstimates . mcEstimates . mergeEstimationRes . metricNames . metricsSummary . pairedComparisons . performanceEstimation . rankWorkflows . regressionMetrics . responseValues . results2table . runWorkflow . signifDiffs . smote . standardPOST . standardPRE . standardWF . subset-methods . taskNames . timeseriesWF . topPerformer . topPerformers . workflowNames . workflowVariants .
Some associated R codes: classDefs.R . evaluationMetrics.R . experiments.R . methods.R . resultsAnalysis.R . resultsManipulation.R . smote.R . workflows.R . Full performanceEstimation package functions and examples
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