Synthesis of microarray-based classification

Documentation for package ‘CMA’ version 1.65.0

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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"