CMA-package             Synthesis of microarray-based classification
ElasticNetCMA           Classfication and variable selection by the
                        ElasticNet
ElasticNetCMA-methods   Classfication and variable selection by the
                        ElasticNet
GeneSelection           General method for variable selection with
                        various methods
GeneSelection-methods   General method for variable selection with
                        various methods
GenerateLearningsets    Repeated Divisions into learn- and tets sets
LassoCMA                L1 penalized logistic regression
LassoCMA-methods        L1 penalized logistic regression
Planarplot              Visualize Separability of different classes
Planarplot-methods      Visualize Separability of different classes
best                    Show best hyperparameter settings
boxplot,evaloutput-method
                        Make a boxplot of the classifier evaluation
classification          General method for classification with various
                        methods
classification-methods
                        General method for classification with various
                        methods
cloutput-class          "cloutput"
clvarseloutput-class    "clvarseloutput"
compBoostCMA            Componentwise Boosting
compBoostCMA-methods    Componentwise Boosting
compare                 Compare different classifiers
compare-methods         Compare different classifiers
dldaCMA                 Diagonal Discriminant Analysis
dldaCMA-methods         Diagonal Discriminant Analysis
evaloutput-class        "evaloutput"
evaluation              Evaluation of classifiers
evaluation-methods      Evaluation of classifiers
fdaCMA                  Fisher's Linear Discriminant Analysis
fdaCMA-methods          Fisher's Linear Discriminant Analysis
flexdaCMA               Flexible Discriminant Analysis
flexdaCMA-methods       Flexible Discriminant Analysis
ftable,cloutput-method
                        Cross-tabulation of predicted and true class
                        labels
gbmCMA                  Tree-based Gradient Boosting
gbmCMA-methods          Tree-based Gradient Boosting
genesel-class           "genesel"
golub                   ALL/AML dataset of Golub et al. (1999)
join                    Combine list elements returned by the method
                        classification
join-methods            Combine list elements returned by the method
                        classification
khan                    Small blue round cell tumor dataset of Khan et
                        al. (2001)
knnCMA                  Nearest Neighbours
knnCMA-methods          Nearest Neighbours
ldaCMA                  Linear Discriminant Analysis
ldaCMA-methods          Linear Discriminant Analysis
learningsets-class      "learningsets"
nnetCMA                 Feed-forward Neural Networks
nnetCMA-methods         Feed-Forward Neural Networks
obsinfo                 Classifiability of observations
pknnCMA                 Probabilistic Nearest Neighbours
pknnCMA-methods         Probabilistic nearest neighbours
plot,cloutput-method    Probability plot
plot,genesel-method     Barplot of variable importance
plot,tuningresult-method
                        Visualize results of tuning
plotprob                Internal functions
plrCMA                  L2 penalized logistic regression
plrCMA-methods          L2 penalized logistic regression
pls_ldaCMA              Partial Least Squares combined with Linear
                        Discriminant Analysis
pls_ldaCMA-methods      Partial Least Squares combined with Linear
                        Discriminant Analysis
pls_lrCMA               Partial Least Squares followed by logistic
                        regression
pls_lrCMA-methods       Partial Least Squares followed by logistic
                        regression
pls_rfCMA               Partial Least Squares followed by random
                        forests
pls_rfCMA-methods       Partial Least Squares followed by random
                        forests
pnnCMA                  Probabilistic Neural Networks
pnnCMA-methods          Probabilistic Neural Networks
prediction              General method for predicting classes of new
                        observations
prediction-methods      General method for predicting class lables of
                        new observations
predoutput-class        "predoutput"
qdaCMA                  Quadratic Discriminant Analysis
qdaCMA-methods          Quadratic Discriminant Analysis
rfCMA                   Classification based on Random Forests
rfCMA-methods           Classification based on Random Forests
roc                     Receiver Operator Characteristic
scdaCMA                 Shrunken Centroids Discriminant Analysis
scdaCMA-methods         Shrunken Centroids Discriminant Analysis
shrinkldaCMA            Shrinkage linear discriminant analysis
shrinkldaCMA-methods    Shrinkage linear discriminant analysis
summary,evaloutput-method
                        Summarize classifier evaluation
svmCMA                  Support Vector Machine
svmCMA-methods          Support Vector Machine
toplist                 Display 'top' variables
ttest                   Filter functions for Gene Selection
tune                    Hyperparameter tuning for classifiers
tune-methods            Hyperparameter tuning for classifiers
tuningresult-class      "tuningresult"
varseloutput-class      "varseloutput"
weighted.mcr            Tuning / Selection bias correction
weighted.mcr-methods    General method for tuning / selection bias
                        correction
wmc                     Tuning / Selection bias correction based on
                        matrix of subsampling fold errors
wmc-methods             General method for tuning / selection bias
                        correction based on a matrix of subsampling
                        fold errors.
wmcr.result-class       "wmcr.result"
