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ECoL  

Complexity Measures for Supervised Problems
View on CRAN: Click here


Download and install ECoL package within the R console
Install from CRAN:
install.packages("ECoL")

Install from Github:
library("remotes")
install_github("cran/ECoL")

Install by package version:
library("remotes")
install_version("ECoL", "0.3.0")



Attach the package and use:
library("ECoL")
Maintained by
Luis Garcia
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-01-22
Latest Update: 2019-11-05
Description:
Provides measures to characterize the complexity of classification and regression problems based on aspects that quantify the linearity of the data, the presence of informative feature, the sparsity and dimensionality of the datasets. This package provides bug fixes, generalizations and implementations of many state of the art measures. The measures are described in the papers: Lorena et al. (2019) and Lorena et al. (2018) .
How to cite:
Luis Garcia (2018). ECoL: Complexity Measures for Supervised Problems. R package version 0.3.0, https://cran.r-project.org/web/packages/ECoL. Accessed 21 Nov. 2024.
Previous versions and publish date:
0.1.0 (2018-01-22 15:53), 0.2.0 (2019-02-26 22:10)
Other packages that cited ECoL R package
View ECoL citation profile
Other R packages that ECoL depends, imports, suggests or enhances
Complete documentation for ECoL
Functions, R codes and Examples using the ECoL R package
Some associated functions: balance . complexity . correlation . dimensionality . linearity . neighborhood . network . overlapping . smoothness . summarization . 
Some associated R codes: balance.R . complexity.R . correlation.R . dimensionality.R . internal.R . linearity.R . neighborhood.R . network.R . overlapping.R . smoothness.R . summarization.R .  Full ECoL package functions and examples
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