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mlearning
View on CRAN: Click
here
Download and install mlearning package within the R console
Install from CRAN:
install.packages("mlearning")
Install from Github:
library("remotes")
install_github("cran/mlearning")
Install by package version:
library("remotes")
install_version("mlearning", "1.2.1")
Attach the package and use:
library("mlearning")
Maintained by
Philippe Grosjean
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2013-01-30
Latest Update: 2023-08-30
Description:
A unified interface is provided to various machine learning
algorithms like linear or quadratic discriminant analysis, k-nearest
neighbors, random forest, support vector machine, ... It allows to train,
test, and apply cross-validation using similar functions and function
arguments with a minimalist and clean, formula-based interface. Missing data
are processed the same way as base and stats R functions for all algorithms,
both in training and testing. Confusion matrices are also provided with a rich
set of metrics calculated and a few specific plots.
How to cite:
Philippe Grosjean (2013). mlearning: Machine Learning Algorithms with Unified Interface and Confusion Matrices. R package version 1.2.1, https://cran.r-project.org/web/packages/mlearning. Accessed 22 Dec. 2024.
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Other R packages that mlearning depends,
imports, suggests or enhances
Complete documentation for mlearning
Functions, R codes and Examples using
the mlearning R package
Some associated functions: confusion . mlKnn . mlLda . mlLvq . mlNaiveBayes . mlNnet . mlQda . mlRforest . mlRpart . mlSvm . mlearning-package . mlearning . plot.confusion . prior . response . train .
Some associated R codes: confusion.R . ml_knn.R . ml_lda.R . ml_lvq.R . ml_naive_bayes.R . ml_nnet.R . ml_qda.R . ml_rforest.R . ml_rpart.R . ml_svm.R . mlearning-package.R . mlearning.R . plot.confusion.R . prior.R . response.R . train.R . Full mlearning package functions and examples
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