Title: Interface to the National Lakes Assessment
Authors@R: person("Joseph", "Stachelek", email = "stachel2@msu.edu", role = c("aut", "cre"))
Description: Client for programmatic access to the 2007 and 2012 National
containing data for hundreds of lakes in the lower 48 states of the contiguous US.
Suggests: knitr, rmarkdown, dplyr, magrittr, skimr, sf, maps, R.rsp

Package: nlcv
Type: Package
Title: Nested Loop Cross Validation
Version: 0.3.2
Date: 2017-10-19
Author: Willem Talloen, Tobias Verbeke
Maintainer: Laure Cougnaud <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
License: GPL-3
RoxygenNote: 6.0.1.9000
NeedsCompilation: no
Packaged: 2017-10-19 14:31:04 UTC; lcougnaud
Repository: CRAN
Date/Publication: 2017-10-19 17:32:45 UTC

Package: nlcv
Type: Package
Title: Nested Loop Cross Validation
Version: 0.3.3
Date: 2018-05-04
Author: Willem Talloen, Tobias Verbeke
Maintainer: Laure Cougnaud <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
License: GPL-3
RoxygenNote: 6.0.1.9000
NeedsCompilation: no
Packaged: 2018-05-04 17:58:07 UTC; lcougnaud
Repository: CRAN
Date/Publication: 2018-05-04 18:19:05 UTC