Package: nlcv
Type: Package
Title: Nested Loop Cross Validation
Version: 0.3.6
Date: 2025-05-06
Authors@R: c(
  person(given = "Willem", family = "Talloen", role = "aut"),
  person(given = "Tobias", family = "Verbeke", role = "aut"),
  person(given = "Laure", family = "Cougnaud", role = "cre", 
  email = "laure.cougnaud@openanalytics.eu"))
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) 
  <doi:10.2202/1544-6115.1078>.
Depends: R (>= 2.10), a4Core, MLInterfaces (>= 1.22.0), xtable
Imports: limma, MASS, methods, graphics, Biobase, multtest,
        RColorBrewer, pamr, randomForest, ROCR, ipred, e1071, kernlab
Suggests: RUnit, ALL
License: GPL-3
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2025-05-06 20:24:23 UTC; lcougnaud
Author: Willem Talloen [aut],
  Tobias Verbeke [aut],
  Laure Cougnaud [cre]
Maintainer: Laure Cougnaud <laure.cougnaud@openanalytics.eu>
Repository: CRAN
Date/Publication: 2025-05-06 21:00:02 UTC
Built: R 4.6.0; ; 2026-04-10 03:08:36 UTC; windows
