Synthesis of microarray-based classification


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Documentation for package ‘CMA’ version 1.65.0

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B C D E F G J K L M N O P Q R S T V W

CMA-package Synthesis of microarray-based classification

-- B --

best Show best hyperparameter settings
best-method Show best hyperparameter settings
bklr Internal functions
bklr.predict Internal functions
bkreg Internal functions
boxplot-method Make a boxplot of the classifier evaluation

-- C --

care.dev Internal functions
care.exp Internal functions
characterplot Internal functions
classification General method for classification with various methods
classification-method General method for classification with various methods
classification-methods General method for classification with various methods
cloutput "cloutput"
cloutput-class "cloutput"
clvarseloutput "clvarseloutput"
clvarseloutput-class "clvarseloutput"
CMA Synthesis of microarray-based classification
compare Compare different classifiers
compare-method Compare different classifiers
compare-methods Compare different classifiers
compBoostCMA Componentwise Boosting
compBoostCMA-method Componentwise Boosting
compBoostCMA-methods Componentwise Boosting

-- D --

dldaCMA Diagonal Discriminant Analysis
dldaCMA-method Diagonal Discriminant Analysis
dldaCMA-methods Diagonal Discriminant Analysis

-- E --

ElasticNetCMA Classfication and variable selection by the ElasticNet
ElasticNetCMA-method Classfication and variable selection by the ElasticNet
ElasticNetCMA-methods Classfication and variable selection by the ElasticNet
evaloutput "evaloutput"
evaloutput-class "evaloutput"
evaluation Evaluation of classifiers
evaluation-method Evaluation of classifiers
evaluation-methods Evaluation of classifiers

-- F --

fdaCMA Fisher's Linear Discriminant Analysis
fdaCMA-method Fisher's Linear Discriminant Analysis
fdaCMA-methods Fisher's Linear Discriminant Analysis
flexdaCMA Flexible Discriminant Analysis
flexdaCMA-method Flexible Discriminant Analysis
flexdaCMA-methods Flexible Discriminant Analysis
ftable-method Cross-tabulation of predicted and true class labels
ftest Filter functions for Gene Selection

-- G --

gbmCMA Tree-based Gradient Boosting
gbmCMA-method Tree-based Gradient Boosting
gbmCMA-methods Tree-based Gradient Boosting
GenerateLearningsets Repeated Divisions into learn- and tets sets
genesel "genesel"
genesel-class "genesel"
GeneSelection General method for variable selection with various methods
GeneSelection-method 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)
golubcrit Filter functions for Gene Selection

-- J --

join Combine list elements returned by the method classification
join-method Combine list elements returned by the method classification
join-methods Combine list elements returned by the method classification

-- K --

khan Small blue round cell tumor dataset of Khan et al. (2001)
knnCMA Nearest Neighbours
knnCMA-method Nearest Neighbours
knnCMA-methods Nearest Neighbours
kruskaltest Filter functions for Gene Selection

-- L --

LassoCMA L1 penalized logistic regression
LassoCMA-method L1 penalized logistic regression
LassoCMA-methods L1 penalized logistic regression
ldaCMA Linear Discriminant Analysis
ldaCMA-method Linear Discriminant Analysis
ldaCMA-methods Linear Discriminant Analysis
learningsets "learningsets"
learningsets-class "learningsets"
limmatest Filter functions for Gene Selection

-- M --

mklr Internal functions
mklr.predict Internal functions
mkreg Internal functions
my.care.exp Internal functions

-- N --

nnetCMA Feed-forward Neural Networks
nnetCMA-method Feed-Forward Neural Networks
nnetCMA-methods Feed-Forward Neural Networks

-- O --

obsinfo Classifiability of observations
obsinfo-method "evaloutput"

-- P --

pknnCMA Probabilistic Nearest Neighbours
pknnCMA-method Probabilistic nearest neighbours
pknnCMA-methods Probabilistic nearest neighbours
Planarplot Visualize Separability of different classes
Planarplot-method Visualize Separability of different classes
Planarplot-methods Visualize Separability of different classes
plot-method Probability plot
plot-method Barplot of variable importance
plot-method Visualize results of tuning
plotprob Internal functions
plrCMA L2 penalized logistic regression
plrCMA-method L2 penalized logistic regression
plrCMA-methods L2 penalized logistic regression
pls_ldaCMA Partial Least Squares combined with Linear Discriminant Analysis
pls_ldaCMA-method 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-method 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-method Partial Least Squares followed by random forests
pls_rfCMA-methods Partial Least Squares followed by random forests
pnnCMA Probabilistic Neural Networks
pnnCMA-method Probabilistic Neural Networks
pnnCMA-methods Probabilistic Neural Networks
prediction General method for predicting classes of new observations
prediction-method General method for predicting class lables of new observations
prediction-methods General method for predicting class lables of new observations
predoutput "predoutput"
predoutput-class "predoutput"

-- Q --

qdaCMA Quadratic Discriminant Analysis
qdaCMA-method Quadratic Discriminant Analysis
qdaCMA-methods Quadratic Discriminant Analysis

-- R --

rfCMA Classification based on Random Forests
rfCMA-method Classification based on Random Forests
rfCMA-methods Classification based on Random Forests
rfe Filter functions for Gene Selection
roc Receiver Operator Characteristic
roc-method Receiver Operator Characteristic
ROCinternal Internal functions
roundvector Internal functions
rowswaps Internal functions

-- S --

safeexp Internal functions
scdaCMA Shrunken Centroids Discriminant Analysis
scdaCMA-method Shrunken Centroids Discriminant Analysis
scdaCMA-methods Shrunken Centroids Discriminant Analysis
show-method "cloutput"
show-method "evaloutput"
show-method "genesel"
show-method "learningsets"
show-method "predoutput"
show-method "tuningresult"
show-method "wmcr.result"
shrinkcat Filter functions for Gene Selection
shrinkldaCMA Shrinkage linear discriminant analysis
shrinkldaCMA-method Shrinkage linear discriminant analysis
shrinkldaCMA-methods Shrinkage linear discriminant analysis
summary-method Summarize classifier evaluation
svmCMA Support Vector Machine
svmCMA-method Support Vector Machine
svmCMA-methods Support Vector Machine

-- T --

toplist Display 'top' variables
toplist-method Display 'top' variables
ttest Filter functions for Gene Selection
tune Hyperparameter tuning for classifiers
tune-method Hyperparameter tuning for classifiers
tune-methods Hyperparameter tuning for classifiers
tuningresult "tuningresult"
tuningresult-class "tuningresult"

-- V --

varseloutput "varseloutput"
varseloutput-class "varseloutput"

-- W --

weighted.mcr Tuning / Selection bias correction
weighted.mcr-method General method for tuning / selection bias correction
weighted.mcr-methods General method for tuning / selection bias correction
welchtest Filter functions for Gene Selection
wilcoxtest Filter functions for Gene Selection
wmc Tuning / Selection bias correction based on matrix of subsampling fold errors
wmc-method General method for tuning / selection bias correction based on a matrix of subsampling fold errors.
wmc-methods General method for tuning / selection bias correction based on a matrix of subsampling fold errors.
wmcr.result "wmcr.result"
wmcr.result-class "wmcr.result"