CMA: Synthesis of microarray-based classification

This package provides a comprehensive collection of various microarray-based classification algorithms both from Machine Learning and Statistics. Variable Selection, Hyperparameter tuning, Evaluation and Comparison can be performed combined or stepwise in a user-friendly environment.

Author
Martin Slawski <ms@cs.uni-sb.de>, Anne-Laure Boulesteix <boulesteix@ibe.med.uni-muenchen.de>, Christoph Bernau <bernau@ibe.med.uni-muenchen.de>.
Date of publication
None
Maintainer
Christoph Bernau <bernau@ibe.med.uni-muenchen.de>
License
GPL (>= 2)
Version
1.32.0

View on Bioconductor

Man pages

best
Show best hyperparameter settings
boxplot
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"
CMA-package
Synthesis of microarray-based classification
compare
Compare different classifiers
compare-methods
Compare different classifiers
compBoostCMA
Componentwise Boosting
compBoostCMA-methods
Componentwise Boosting
dldaCMA
Diagonal Discriminant Analysis
dldaCMA-methods
Diagonal Discriminant Analysis
ElasticNetCMA
Classfication and variable selection by the ElasticNet
ElasticNetCMA-methods
Classfication and variable selection by the ElasticNet
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
Cross-tabulation of predicted and true class labels
gbmCMA
Tree-based Gradient Boosting
gbmCMA-methods
Tree-based Gradient Boosting
GenerateLearningsets
Repeated Divisions into learn- and tets sets
genesel-class
"genesel"
GeneSelection
General method for variable selection with various methods
GeneSelection-methods
General method for variable selection with various methods
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
LassoCMA
L1 penalized logistic regression
LassoCMA-methods
L1 penalized logistic regression
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
Planarplot
Visualize Separability of different classes
Planarplot-methods
Visualize Separability of different classes
plot,cloutput-method
Probability plot
plot,genesel-method
Barplot of variable importance
plot,tuningresult-method
Visualize results of tuning
plrCMA
L2 penalized logistic regression
plrCMA-methods
L2 penalized logistic regression
pls_ldaCMA
Partial Least Squares combined with Linear Discriminant...
pls_ldaCMA-methods
Partial Least Squares combined with Linear Discriminant...
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-methods
Probabilistic Neural Networks
prediction
General method for predicting classes of new observations
prediction-methods
General method for predicting class lables of new...
predoutput-class
"predoutput"
qdaCMA-methods
Quadratic Discriminant Analysis
rfCMA
Classification based on Random Forests
rfCMA-methods
Classification based on Random Forests
roc
Receiver Operator Characteristic
scdaCMA-methods
Shrunken Centroids Discriminant Analysis
shrinkldaCMA
Shrinkage linear discriminant analysis
shrinkldaCMA-methods
Shrinkage linear discriminant analysis
summary
Summarize classifier evaluation
svmCMA
Support Vector Machine
svmCMA-methods
Support Vector Machine
toplist
Display 'top' variables
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...
wmc-methods
General method for tuning / selection bias correction based...
wmcr_result-class
"wmcr.result"

Files in this package

CMA/DESCRIPTION
CMA/NAMESPACE
CMA/R
CMA/R/ElasticNetCMA.r
CMA/R/GeneSelection.r
CMA/R/GenerateLearningsets.r
CMA/R/LassoCMA.r
CMA/R/Planarplot.r
CMA/R/classes.r
CMA/R/classification.r
CMA/R/compBoostCMA.r
CMA/R/compare.r
CMA/R/dldaCMA.r
CMA/R/evaluation.r
CMA/R/fdaCMA.r
CMA/R/filter.r
CMA/R/flexdaCMA.r
CMA/R/gbmCMA.r
CMA/R/internals.r
CMA/R/join.r
CMA/R/knnCMA.r
CMA/R/ldaCMA.r
CMA/R/nnetCMA.r
CMA/R/pknnCMA.r
CMA/R/plrCMA.r
CMA/R/pls_ldaCMA.r
CMA/R/pls_lrCMA.r
CMA/R/pls_rfCMA.r
CMA/R/pnnCMA.r
CMA/R/qdaCMA.r
CMA/R/rfCMA.r
CMA/R/scdaCMA.r
CMA/R/shrinkldaCMA.r
CMA/R/svmCMA.r
CMA/R/tune.r
CMA/R/weighted_mcr.r
CMA/R/wmc.r
CMA/build
CMA/build/vignette.rds
CMA/data
CMA/data/golub.rda
CMA/data/khan.rda
CMA/inst
CMA/inst/doc
CMA/inst/doc/CMA_vignette.R
CMA/inst/doc/CMA_vignette.pdf
CMA/inst/doc/CMA_vignette.rnw
CMA/man
CMA/man/CMA-package.Rd
CMA/man/ElasticNetCMA-methods.Rd
CMA/man/ElasticNetCMA.Rd
CMA/man/GeneSelection-methods.Rd
CMA/man/GeneSelection.Rd
CMA/man/GenerateLearningsets.Rd
CMA/man/LassoCMA-methods.Rd
CMA/man/LassoCMA.Rd
CMA/man/Planarplot-methods.Rd
CMA/man/Planarplot.Rd
CMA/man/best.Rd
CMA/man/boxplot.Rd
CMA/man/classification-methods.Rd
CMA/man/classification.Rd
CMA/man/cloutput-class.Rd
CMA/man/clvarseloutput-class.Rd
CMA/man/compBoostCMA-methods.Rd
CMA/man/compBoostCMA.Rd
CMA/man/compare-methods.Rd
CMA/man/compare.Rd
CMA/man/dldaCMA-methods.Rd
CMA/man/dldaCMA.Rd
CMA/man/evaloutput-class.Rd
CMA/man/evaluation-methods.Rd
CMA/man/evaluation.Rd
CMA/man/fdaCMA-methods.Rd
CMA/man/fdaCMA.Rd
CMA/man/filter.rd
CMA/man/flexdaCMA-methods.Rd
CMA/man/flexdaCMA.Rd
CMA/man/ftable.Rd
CMA/man/gbmCMA-methods.Rd
CMA/man/gbmCMA.Rd
CMA/man/genesel-class.Rd
CMA/man/golub.Rd
CMA/man/internals.rd
CMA/man/join-methods.Rd
CMA/man/join.Rd
CMA/man/khan.Rd
CMA/man/knnCMA-methods.Rd
CMA/man/knnCMA.Rd
CMA/man/ldaCMA-methods.Rd
CMA/man/ldaCMA.rd
CMA/man/learningsets-class.Rd
CMA/man/nnetCMA-methods.Rd
CMA/man/nnetCMA.Rd
CMA/man/obsinfo.Rd
CMA/man/pknnCMA-methods.Rd
CMA/man/pknnCMA.Rd
CMA/man/plot,cloutput-method.Rd
CMA/man/plot,genesel-method.Rd
CMA/man/plot,tuningresult-method.Rd
CMA/man/plrCMA-methods.Rd
CMA/man/plrCMA.Rd
CMA/man/pls_ldaCMA-methods.Rd
CMA/man/pls_ldaCMA.Rd
CMA/man/pls_lrCMA-methods.Rd
CMA/man/pls_lrCMA.rd
CMA/man/pls_rfCMA-methods.Rd
CMA/man/pls_rfCMA.Rd
CMA/man/pnnCMA-methods.Rd
CMA/man/pnnCMA.rd
CMA/man/prediction-methods.Rd
CMA/man/prediction.Rd
CMA/man/predoutput-class.Rd
CMA/man/qdaCMA-methods.Rd
CMA/man/qdaCMA.rd
CMA/man/rfCMA-methods.Rd
CMA/man/rfCMA.Rd
CMA/man/roc.Rd
CMA/man/scdaCMA-methods.Rd
CMA/man/scdaCMA.rd
CMA/man/shrinkldaCMA-methods.Rd
CMA/man/shrinkldaCMA.Rd
CMA/man/summary.Rd
CMA/man/svmCMA-methods.Rd
CMA/man/svmCMA.Rd
CMA/man/toplist.Rd
CMA/man/tune-methods.Rd
CMA/man/tune.Rd
CMA/man/tuningresult-class.Rd
CMA/man/varseloutput-class.Rd
CMA/man/weighted_mcr-methods.Rd
CMA/man/weighted_mcr.Rd
CMA/man/wmc-methods.Rd
CMA/man/wmc.Rd
CMA/man/wmcr_result-class.Rd
CMA/vignettes
CMA/vignettes/CMA_vignette.rnw
CMA/vignettes/classification.bib
CMA/vignettes/preamble.tex