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nlcv  

Nested Loop Cross Validation
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("nlcv", "0.3.6")



Attach the package and use:
library("nlcv")
Maintained by
Laure Cougnaud
[Scholar Profile | Author Map]
First Published: 2017-10-19
Latest Update: 2018-06-29
Description:
Nested loop cross validation for classification purposes for misclassification error rate estimation. The package supports several methodologies for feature selection: random forest, Student t-test, limma, and provides an interface to the following classification methods in the 'MLInterfaces' package: linear, quadratic discriminant analyses, random forest, bagging, prediction analysis for microarray, generalized linear model, support vector machine (svm and ksvm). Visualizations to assess the quality of the classifier are included: plot of the ranks of the features, scores plot for a specific classification algorithm and number of features, misclassification rate for the different number of features and classification algorithms tested and ROC plot. For further details about the methodology, please check: Markus Ruschhaupt, Wolfgang Huber, Annemarie Poustka, and Ulrich Mansmann (2004) .
How to cite:
Laure Cougnaud (2017). nlcv: Nested Loop Cross Validation. R package version 0.3.6, https://cran.r-project.org/web/packages/nlcv. Accessed 11 May. 2025.
Previous versions and publish date:
0.3.2 (2017-10-19 19:32), 0.3.3 (2018-05-04 20:19), 0.3.4 (2018-05-18 14:01), 0.3.5 (2018-06-29 23:50)
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Complete documentation for nlcv
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