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performanceEstimation  

An Infra-Structure for Performance Estimation of Predictive Models
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]
All associated links for this package
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 21 Nov. 2024.
Previous versions and publish date:
0.1.1 (2014-03-11 19:31), 0.1 (2013-12-29 14:54), 1.0.0 (2014-12-06 00:05), 1.0.1 (2015-06-17 01:45), 1.0.2 (2015-09-07 18:18)
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