Package: CMA 1.65.0

Roman Hornung

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.

Authors:Martin Slawski <[email protected]>, Anne-Laure Boulesteix <[email protected]>, Christoph Bernau <[email protected]>.

CMA_1.65.0.tar.gz
CMA_1.65.0.zip(r-4.5)CMA_1.65.0.zip(r-4.4)CMA_1.65.0.zip(r-4.3)
CMA_1.65.0.tgz(r-4.4-any)CMA_1.65.0.tgz(r-4.3-any)
CMA_1.65.0.tar.gz(r-4.5-noble)CMA_1.65.0.tar.gz(r-4.4-noble)
CMA_1.65.0.tgz(r-4.4-emscripten)CMA_1.65.0.tgz(r-4.3-emscripten)
CMA.pdf |CMA.html✨
CMA/json (API)

# Install 'CMA' in R:
install.packages('CMA', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • golub - ALL/AML dataset of Golub et al.
  • khan - Small blue round cell tumor dataset of Khan et al.

On BioConductor:CMA-1.65.0(bioc 3.21)CMA-1.64.0(bioc 3.20)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

classificationdecisiontree

5.09 score 61 scripts 324 downloads 337 mentions 49 exports 3 dependencies

Last updated 23 days agofrom:c6f5e4f1f1. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 07 2024
R-4.5-winNOTENov 07 2024
R-4.5-linuxNOTENov 07 2024
R-4.4-winNOTENov 07 2024
R-4.4-macNOTENov 07 2024
R-4.3-winNOTENov 07 2024
R-4.3-macNOTENov 07 2024

Exports:bestboxplotclassificationcomparecompBoostCMAdldaCMAElasticNetCMAevaluationfdaCMAflexdaCMAftableftestgbmCMAGenerateLearningsetsGeneSelectiongolubcritjoinknnCMAkruskaltestLassoCMAldaCMAlimmatestnnetCMAobsinfopknnCMAPlanarplotplotplrCMApls_ldaCMApls_lrCMApls_rfCMApnnCMApredictionqdaCMArfCMArferocscdaCMAshowshrinkldaCMAsummarysvmCMAtoplistttesttuneweighted.mcrwelchtestwilcoxtestwmc

Dependencies:BiobaseBiocGenericsgenerics

CMA Manual

Rendered fromCMA_vignette.rnwusingutils::Sweaveon Nov 07 2024.

Last update: 2013-11-01
Started: 2013-11-01

Readme and manuals

Help Manual

Help pageTopics
Synthesis of microarray-based classificationCMA-package CMA
Barplot of variable importanceplot,genesel,missing-method plot,genesel-method
Show best hyperparameter settingsbest best,tuningresult-method
Make a boxplot of the classifier evaluationboxplot,evaloutput-method
General method for classification with various methodsclassification
General method for classification with various methodsclassification,data.frame,missing,formula-method classification,ExpressionSet,character,missing-method classification,matrix,factor,missing-method classification,matrix,numeric,missing-method classification-methods
"cloutput"cloutput cloutput-class show,cloutput-method
"clvarseloutput"clvarseloutput clvarseloutput-class
Compare different classifierscompare
Compare different classifierscompare,list-method compare-methods
Componentwise BoostingcompBoostCMA
Componentwise BoostingcompBoostCMA,data.frame,missing,formula-method compBoostCMA,ExpressionSet,character,missing-method compBoostCMA,matrix,factor,missing-method compBoostCMA,matrix,numeric,missing-method compBoostCMA-methods
Diagonal Discriminant AnalysisdldaCMA
Diagonal Discriminant AnalysisdldaCMA,data.frame,missing,formula-method dldaCMA,ExpressionSet,character,missing-method dldaCMA,matrix,factor,missing-method dldaCMA,matrix,numeric,missing-method dldaCMA-methods
Classfication and variable selection by the ElasticNetElasticNetCMA
Classfication and variable selection by the ElasticNetElasticNetCMA,data.frame,missing,formula-method ElasticNetCMA,ExpressionSet,character,missing-method ElasticNetCMA,matrix,factor,missing-method ElasticNetCMA,matrix,numeric,missing-method ElasticNetCMA-methods
"evaloutput"evaloutput evaloutput-class obsinfo,evaloutput-method show,evaloutput-method
Evaluation of classifiersevaluation
Evaluation of classifiersevaluation,list-method evaluation-methods
Fisher's Linear Discriminant AnalysisfdaCMA
Fisher's Linear Discriminant AnalysisfdaCMA,data.frame,missing,formula-method fdaCMA,ExpressionSet,character,missing-method fdaCMA,matrix,factor,missing-method fdaCMA,matrix,numeric,missing-method fdaCMA-methods
Filter functions for Gene Selectionftest golubcrit kruskaltest limmatest rfe shrinkcat ttest welchtest wilcoxtest
Flexible Discriminant AnalysisflexdaCMA
Flexible Discriminant AnalysisflexdaCMA,data.frame,missing,formula-method flexdaCMA,ExpressionSet,character,missing-method flexdaCMA,matrix,factor,missing-method flexdaCMA,matrix,numeric,missing-method flexdaCMA-methods
Cross-tabulation of predicted and true class labelsftable,cloutput-method
Tree-based Gradient BoostinggbmCMA
Tree-based Gradient BoostinggbmCMA,data.frame,missing,formula-method gbmCMA,ExpressionSet,character,missing-method gbmCMA,matrix,factor,missing-method gbmCMA,matrix,numeric,missing-method gbmCMA-methods
Repeated Divisions into learn- and tets setsGenerateLearningsets
"genesel"genesel genesel-class show,genesel-method
General method for variable selection with various methodsGeneSelection
General method for variable selection with various methodsGeneSelection,data.frame,missing,formula-method GeneSelection,ExpressionSet,character,missing-method GeneSelection,matrix,factor,missing-method GeneSelection,matrix,numeric,missing-method GeneSelection-methods
ALL/AML dataset of Golub et al. (1999)golub
Internal functionsbklr bklr.predict bkreg care.dev care.exp characterplot mklr mklr.predict mkreg my.care.exp plotprob ROCinternal roundvector rowswaps safeexp
Combine list elements returned by the method classificationjoin
Combine list elements returned by the method classificationjoin,list-method join-methods
Small blue round cell tumor dataset of Khan et al. (2001)khan
Nearest NeighboursknnCMA
Nearest NeighboursknnCMA,data.frame,missing,formula-method knnCMA,ExpressionSet,character,missing-method knnCMA,matrix,factor,missing-method knnCMA,matrix,numeric,missing-method knnCMA-methods
L1 penalized logistic regressionLassoCMA
L1 penalized logistic regressionLassoCMA,data.frame,missing,formula-method LassoCMA,ExpressionSet,character,missing-method LassoCMA,matrix,factor,missing-method LassoCMA,matrix,numeric,missing-method LassoCMA-methods
Linear Discriminant AnalysisldaCMA
Linear Discriminant AnalysisldaCMA,data.frame,missing,formula-method ldaCMA,ExpressionSet,character,missing-method ldaCMA,matrix,factor,missing-method ldaCMA,matrix,numeric,missing-method ldaCMA-methods
"learningsets"learningsets learningsets-class show,learningsets-method
Feed-forward Neural NetworksnnetCMA
Feed-Forward Neural NetworksnnetCMA,data.frame,missing,formula-method nnetCMA,ExpressionSet,character,missing-method nnetCMA,matrix,factor,missing-method nnetCMA,matrix,numeric,missing-method nnetCMA-methods
Classifiability of observationsobsinfo
Probabilistic Nearest NeighbourspknnCMA
Probabilistic nearest neighbourspknnCMA,data.frame,missing,formula-method pknnCMA,ExpressionSet,character,missing-method pknnCMA,matrix,factor,missing-method pknnCMA,matrix,numeric,missing-method pknnCMA-methods
Visualize Separability of different classesPlanarplot
Visualize Separability of different classesPlanarplot,data.frame,missing,formula-method Planarplot,ExpressionSet,character,missing-method Planarplot,matrix,factor,missing-method Planarplot,matrix,numeric,missing-method Planarplot-methods
Probability plotplot,cloutput,missing-method plot,cloutput-method
Visualize results of tuningplot,tuningresult,missing-method plot,tuningresult-method
L2 penalized logistic regressionplrCMA
L2 penalized logistic regressionplrCMA,data.frame,missing,formula-method plrCMA,ExpressionSet,character,missing-method plrCMA,matrix,factor,missing-method plrCMA,matrix,numeric,missing-method plrCMA-methods
Partial Least Squares combined with Linear Discriminant Analysispls_ldaCMA
Partial Least Squares combined with Linear Discriminant Analysispls_ldaCMA,data.frame,missing,formula-method pls_ldaCMA,ExpressionSet,character,missing-method pls_ldaCMA,matrix,factor,missing-method pls_ldaCMA,matrix,numeric,missing-method pls_ldaCMA-methods
Partial Least Squares followed by logistic regressionpls_lrCMA
Partial Least Squares followed by logistic regressionpls_lrCMA,data.frame,missing,formula-method pls_lrCMA,ExpressionSet,character,missing-method pls_lrCMA,matrix,factor,missing-method pls_lrCMA,matrix,numeric,missing-method pls_lrCMA-methods
Partial Least Squares followed by random forestspls_rfCMA
Partial Least Squares followed by random forestspls_rfCMA,data.frame,missing,formula-method pls_rfCMA,ExpressionSet,character,missing-method pls_rfCMA,matrix,factor,missing-method pls_rfCMA,matrix,numeric,missing-method pls_rfCMA-methods
Probabilistic Neural NetworkspnnCMA
Probabilistic Neural NetworkspnnCMA,data.frame,missing,formula-method pnnCMA,ExpressionSet,character,missing-method pnnCMA,matrix,factor,missing-method pnnCMA,matrix,numeric,missing-method pnnCMA-methods
General method for predicting classes of new observationsprediction
General method for predicting class lables of new observationsprediction,data.frame,missing,data.frame,formula-method prediction,ExpressionSet,character,ExpressionSet,missing-method prediction,matrix,ANY,matrix,missing-method prediction-methods
"predoutput"predoutput predoutput-class show,predoutput-method
Quadratic Discriminant AnalysisqdaCMA
Quadratic Discriminant AnalysisqdaCMA,data.frame,missing,formula-method qdaCMA,ExpressionSet,character,missing-method qdaCMA,matrix,factor,missing-method qdaCMA,matrix,numeric,missing-method qdaCMA-methods
Classification based on Random ForestsrfCMA
Classification based on Random ForestsrfCMA,data.frame,missing,formula-method rfCMA,ExpressionSet,character,missing-method rfCMA,matrix,factor,missing-method rfCMA,matrix,numeric,missing-method rfCMA-methods
Receiver Operator Characteristicroc roc,cloutput-method
Shrunken Centroids Discriminant AnalysisscdaCMA
Shrunken Centroids Discriminant AnalysisscdaCMA,data.frame,missing,formula-method scdaCMA,ExpressionSet,character,missing-method scdaCMA,matrix,factor,missing-method scdaCMA,matrix,numeric,missing-method scdaCMA-methods
Shrinkage linear discriminant analysisshrinkldaCMA
Shrinkage linear discriminant analysisshrinkldaCMA,data.frame,missing,formula-method shrinkldaCMA,ExpressionSet,character,missing-method shrinkldaCMA,matrix,factor,missing-method shrinkldaCMA,matrix,numeric,missing-method shrinkldaCMA-methods
Summarize classifier evaluationsummary,evaloutput-method
Support Vector MachinesvmCMA
Support Vector MachinesvmCMA,data.frame,missing,formula-method svmCMA,ExpressionSet,character,missing-method svmCMA,matrix,factor,missing-method svmCMA,matrix,numeric,missing-method svmCMA-methods
Display 'top' variablestoplist toplist,genesel-method
Hyperparameter tuning for classifierstune
Hyperparameter tuning for classifierstune,data.frame,missing,formula-method tune,ExpressionSet,character,missing-method tune,matrix,factor,missing-method tune,matrix,numeric,missing-method tune-methods
"tuningresult"show,tuningresult-method tuningresult tuningresult-class
"varseloutput"varseloutput varseloutput-class
Tuning / Selection bias correctionweighted.mcr
General method for tuning / selection bias correctionweighted.mcr,character,character,missing,character,matrix,factor-method weighted.mcr,character,character,numeric,character,matrix,factor-method weighted.mcr,character,character,numeric,character,matrix,numeric-method weighted.mcr-methods
Tuning / Selection bias correction based on matrix of subsampling fold errorswmc
General method for tuning / selection bias correction based on a matrix of subsampling fold errors.wmc,matrix,numeric,numeric-method wmc-methods
"wmcr.result"show,wmcr.result-method wmcr.result wmcr.result-class