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>.
| Version: | 0.3.2 |
| Depends: | R (≥ 2.10), a4Core, MLInterfaces (≥ 1.22.0), xtable |
| Imports: | limma, MASS, methods, graphics, Biobase, multtest, RColorBrewer, pamr, randomForest, ROCR, ipred, e1071, kernlab |
| Published: | 2017-10-19 |
| Author: | Willem Talloen, Tobias Verbeke |
| Maintainer: | Laure Cougnaud <laure.cougnaud at openanalytics.eu> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | nlcv results |
| Reference manual: | nlcv.pdf |
| Vignettes: |
nlcv |
| Package source: | nlcv_0.3.2.tar.gz |
| Windows binaries: | r-devel: nlcv_0.3.2.zip, r-release: nlcv_0.3.2.zip, r-oldrel: nlcv_0.3.2.zip |
| OS X El Capitan binaries: | r-release: not available |
| OS X Mavericks binaries: | r-oldrel: nlcv_0.3.2.tgz |
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