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Statistics and Machine Learning Toolbox Functions

Alphabetical List By Category
addedvarplotAdded variable plot
addKEvaluate additional numbers of clusters
addlevelsAdd levels to nominal or ordinal arrays
addTermsAdd terms to linear regression model
addTermsAdd terms to generalized linear model
adtestAnderson-Darling test
andrewsplotAndrews plot
anovaAnalysis of variance for between-subject effects
anovaAnalysis of variance for linear mixed-effects model
anovaAnalysis of variance for generalized linear mixed-effects model
anovaAnalysis of variance for linear model
anova1One-way analysis of variance
anova2Two-way analysis of variance
anovanN-way analysis of variance
ansaribradleyAnsari-Bradley test
aoctoolInteractive analysis of covariance
barttestBartlett’s test
BayesianOptimizationBayesian optimization results
bayesoptSelect optimal machine learning hyperparameters using Bayesian optimization
bbdesignBox-Behnken design
bestPointBest point in a Bayesian optimization according to a criterion
betacdfBeta cumulative distribution function
BetaDistributionBeta probability distribution object
betafitBeta parameter estimates
betainvBeta inverse cumulative distribution function
betalikeBeta negative log-likelihood
betapdfBeta probability density function
betarndBeta random numbers
betastatBeta mean and variance
binocdfBinomial cumulative distribution function
binofitBinomial parameter estimates
binoinvBinomial inverse cumulative distribution function
BinomialDistributionBinomial probability distribution object
binopdfBinomial probability density function
binorndBinomial random numbers
binostatBinomial mean and variance
binScatterPlotScatter plot of bins for tall arrays
biplotBiplot
BirnbaumSaundersDistributionBirnbaum-Saunders probability distribution object
bootciBootstrap confidence interval
bootstrpBootstrap sampling
boxplotBox plot
BurrDistributionBurr probability distribution object
CalinskiHarabaszEvaluationCalinski-Harabasz criterion clustering evaluation object
candexchD-optimal design from candidate set using row exchanges
candgenCandidate set generation
canoncorrCanonical correlation
capabilityProcess capability indices
capaplotProcess capability plot
casereadRead case names from file
casewriteWrite case names to file
ccdesignCentral composite design
cdfCumulative distribution functions
cdfplotEmpirical cumulative distribution function plot
cell2datasetConvert cell array to dataset array
chi2cdfChi-square cumulative distribution function
chi2gofChi-square goodness-of-fit test
chi2invChi-square inverse cumulative distribution function
chi2pdfChi-square probability density function
chi2rndChi-square random numbers
chi2statChi-square mean and variance
cholcovCholesky-like covariance decomposition
ClassificationBaggedEnsembleClassification ensemble grown by resampling
ClassificationDiscriminantDiscriminant analysis classification
ClassificationECOCMulticlass model for support vector machines or other classifiers
ClassificationEnsembleEnsemble classifier
ClassificationEnsemble.compactCompact classification ensemble
ClassificationKernelGaussian kernel classification model using feature expansion for big data
ClassificationKNNk-nearest neighbor classification
ClassificationLinearLinear model for binary classification of high-dimensional data
ClassificationNaiveBayesNaive Bayes classification
ClassificationPartitionedECOCCross-validated multiclass model for support vector machines or other classifiers
ClassificationPartitionedEnsembleCross-validated classification ensemble
ClassificationPartitionedLinearCross-validated linear model for binary classification of high-dimensional data
ClassificationPartitionedLinearECOCCross-validated linear error-correcting output codes model for multiclass classification of high-dimensional data
ClassificationPartitionedModelCross-validated classification model
ClassificationSVMSupport vector machine for binary classification
ClassificationTreeBinary decision tree for classification
classregtreeConstruct classification and regression trees
clusterConstruct agglomerative clusters from linkages
clusterConstruct clusters from Gaussian mixture distribution
clusterdataAgglomerative clusters from data
cmdscaleClassical multidimensional scaling
coefCI Confidence intervals for coefficients of linear mixed-effects model
coefCIConfidence intervals for coefficients of generalized linear mixed-effects model
coefCIConfidence intervals of coefficient estimates of linear model
coefCIConfidence intervals of coefficient estimates of generalized linear model
coefCIConfidence intervals of coefficient estimates of nonlinear regression model
coeftestLinear hypothesis test on coefficients of repeated measures model
coefTestHypothesis test on fixed and random effects of linear mixed-effects model
coefTestHypothesis test on fixed and random effects of generalized linear mixed-effects model
coefTestLinear hypothesis test on linear regression model coefficients
coefTestLinear hypothesis test on generalized linear regression model coefficients
coefTestLinear hypothesis test on nonlinear regression model coefficients
combnkEnumeration of combinations
compactCompact clustering evaluation object
compactCompact linear regression model
compactCompact generalized linear regression model
compactCompact support vector machine regression model
compactCreate compact Gaussian process regression model
compactCompact regression tree
compactCompact tree
compactCompact discriminant analysis classifier
compactCompact naive Bayes classifier
compactCompact support vector machine classifier
compactCompact multiclass, error-correcting output codes model
CompactClassificationDiscriminantCompact discriminant analysis class
CompactClassificationECOCCompact multiclass model for support vector machines or other classifiers
CompactClassificationEnsembleCompact classification ensemble class
CompactClassificationNaiveBayesCompact naive Bayes classifier
CompactClassificationSVMCompact support vector machine for binary classification
CompactClassificationTreeCompact classification tree
CompactGeneralizedLinearModelCompact generalized linear regression model class
CompactLinearModelCompact linear regression model class
CompactRegressionEnsembleCompact regression ensemble class
CompactRegressionGPCompact Gaussian process regression model class
CompactRegressionSVMCompact support vector machine regression model
CompactRegressionTreeCompact regression tree
CompactTreeBaggerCompact ensemble of decision trees grown by bootstrap aggregation
CompactTreeBagger.combineCombine two ensembles
CompactTreeBagger.errorError (misclassification probability or MSE)
CompactTreeBagger.marginClassification margin
CompactTreeBagger.mdsproxMultidimensional scaling of proximity matrix
CompactTreeBagger.meanMarginMean classification margin
CompactTreeBagger.outlierMeasureOutlier measure for data
CompactTreeBagger.predictPredict responses using ensemble of bagged decision trees
CompactTreeBagger.proximityProximity matrix for data
CompactTreeBagger.setDefaultYfitSet default value for predict
compareCompare linear mixed-effects models
compareCompare generalized linear mixed-effects models
compareHoldoutCompare accuracies of two classification models using new data
compareHoldoutCompare accuracies of two classification models using new data
compareHoldoutCompare accuracies of two classification models using new data
compareHoldoutCompare accuracies of two models using new data
compareHoldoutCompare accuracies of two classification models using new data
compareHoldoutCompare accuracies of two classification models using new data
compareHoldoutCompare accuracies of two classification models using new data
confusionmatConfusion matrix
controlchartShewhart control charts
controlrulesWestern Electric and Nelson control rules
cophenetCophenetic correlation coefficient
copulacdfCopula cumulative distribution function
copulafitFit copula to data
copulaparamCopula parameters as function of rank correlation
copulapdfCopula probability density function
copularndCopula random numbers
copulastatCopula rank correlation
cordexchCoordinate exchange
corrLinear or rank correlation
corrcovConvert covariance matrix to correlation matrix
covarianceParametersExtract covariance parameters of linear mixed-effects model
covarianceParametersExtract covariance parameters of generalized linear mixed-effects model
coxphfitCox proportional hazards regression
creatensCreate object to use in k-nearest neighbor search
crosstabCross-tabulation
crossvalLoss estimate using cross validation
crossvalCross-validated support vector machine regression model
crossvalCross-validate Gaussian process regression model
crossvalCross-validated decision tree
crossvalCross validate ensemble
crossvalCross-validated decision tree
crossvalCross-validated discriminant analysis classifier
crossvalCross-validated naive Bayes classifier
crossvalCross-validated k-nearest neighbor classifier
crossvalCross-validate multiclass, error-correcting output codes model
crossvalCross-validated support vector machine classifier
crossvalCross validate ensemble
cvlossRegression error by cross validation
cvlossClassification error by cross validation
cvpartitionCreate cross validation partition for data
cvpartitionData partitions for cross validation
cvshrinkCross validate shrinking (pruning) ensemble
cvshrinkCross-validate regularization of linear discriminant
datasampleRandomly sample from data, with or without replacement
datasetArrays for statistical data
dataset2cellConvert dataset array to cell array
dataset2structConvert dataset array to structure
dataset2tableConvert dataset array to table
datasetfunApply function to dataset array variables
daugmentD-optimal augmentation
DaviesBouldinEvaluationDavies-Bouldin criterion clustering evaluation object
dcovaryD-optimal design with fixed covariates
dendrogramDendrogram plot
designecocCoding matrix for reducing error-correcting output code to binary
designMatrixFixed- and random-effects design matrices
designMatrixFixed- and random-effects design matrices
devianceTestAnalysis of deviance
dfittoolOpen Distribution Fitter app
discardSupportVectorsDiscard support vectors
discardSupportVectorsDiscard support vectors of linear support vector machine binary learners
discardSupportVectorsDiscard support vectors for linear support vector machine models
dispDisplay linear regression model
dispDisplay linear mixed-effects model
dispDisplay generalized linear regression model
dispDisplay generalized linear mixed-effects model
dispDisplay nonlinear regression model
distributionFitterOpen Distribution Fitter app
droplevelsDrop levels from a nominal or ordinal array
dummyvarCreate dummy variables
dwtestDurbin-Watson test
dwtestDurbin-Watson test of linear model
ecdfEmpirical cumulative distribution function
ecdfhistHistogram based on empirical cumulative distribution function
edgeClassification edge
edgeClassification edge
edgeClassification edge for naive Bayes classifiers
edgeEdge of k-nearest neighbor classifier
edgeClassification edge for support vector machine classifiers
edgeClassification edge for multiclass, error-correcting output codes model
edgeClassification edge for linear classification models
edgeClassification edge for Gaussian kernel classification model
edgeClassification edge
epsilonEpsilon adjustment for repeated measures anova
evalclustersEvaluate clustering solutions
evcdfExtreme value cumulative distribution function
evfitExtreme value parameter estimates
evinvExtreme value inverse cumulative distribution function
evlikeExtreme value negative log-likelihood
evpdfExtreme value probability density function
evrndExtreme value random numbers
evstatExtreme value mean and variance
ExhaustiveSearcherExhaustive nearest neighbor searcher
ExhaustiveSearcherPrepare exhaustive nearest neighbor searcher
expcdfExponential cumulative distribution function
expfitExponential parameter estimates
expinvExponential inverse cumulative distribution function
explikeExponential negative log-likelihood
ExponentialDistributionExponential probability distribution object
exportWrite dataset array to file
exppdfExponential probability density function
exprndExponential random numbers
expstatExponential mean and variance
ExtremeValueDistributionExtreme value probability distribution object
factoranFactor analysis
fcdfF cumulative distribution function
FeatureSelectionNCAClassificationFeature selection for classification using neighborhood component analysis (NCA)
FeatureSelectionNCARegressionFeature selection for regression using neighborhood component analysis (NCA)
fevalEvaluate linear regression model prediction
fevalEvaluate generalized linear regression model prediction
fevalEvaluate nonlinear regression model prediction
ff2nTwo-level full factorial design
finvF inverse cumulative distribution function
fishertestFisher’s exact test
fitcdiscrFit discriminant analysis classifier
fitcecocFit multiclass models for support vector machines or other classifiers
fitcensembleFit ensemble of learners for classification
fitckernelFit Gaussian kernel classification model using feature expansion for big data
fitcknnFit k-nearest neighbor classifier
fitclinearFit linear classification model to high-dimensional data
fitcnbTrain multiclass naive Bayes model
fitcsvmTrain binary support vector machine classifier
fitctreeFit binary classification decision tree for multiclass classification
fitdistFit probability distribution object to data
fitensembleFit ensemble of learners for classification and regression
fitglmCreate generalized linear regression model
fitglmeFit generalized linear mixed-effects model
fitgmdistFit Gaussian mixture distribution to data
fitlmCreate linear regression model
fitlmeFit linear mixed-effects model
fitlmematrixFit linear mixed-effects model
fitnlmFit nonlinear regression model
fitPosteriorFit posterior probabilities
fitPosteriorFit posterior probabilities
fitrensembleFit ensemble of learners for regression
fitrgpFit a Gaussian process regression (GPR) model
fitrlinearFit linear regression model to high-dimensional data
fitrmFit repeated measures model
fitrsvmFit a support vector machine regression model
fitrtreeFit binary regression decision tree
fitSVMPosteriorFit posterior probabilities
fittedFitted responses from a linear mixed-effects model
fittedFitted responses from generalized linear mixed-effects model
fixedEffectsEstimates of fixed effects and related statistics
fixedEffectsEstimates of fixed effects and related statistics
fpdfF probability density function
fracfactFractional factorial design
fracfactgenFractional factorial design generators
friedmanFriedman’s test
frndF random numbers
fscncaFeature selection using neighborhood component analysis for classification
fsrncaFeature selection using neighborhood component analysis for regression
fstatF mean and variance
fsurfhtInteractive contour plot
fullfactFull factorial design
gagerrGage repeatability and reproducibility study
gamcdfGamma cumulative distribution function
gamfitGamma parameter estimates
gaminvGamma inverse cumulative distribution function
gamlikeGamma negative log-likelihood
GammaDistributionGamma probability distribution object
gampdfGamma probability density function
gamrndGamma random numbers
gamstatGamma mean and variance
GapEvaluationGap criterion clustering evaluation object
GeneralizedExtremeValueDistributionGeneralized extreme value probability distribution object
GeneralizedLinearMixedModelGeneralized linear mixed-effects model class
GeneralizedLinearModelGeneralized linear regression model class
GeneralizedLinearModel.fitCreate generalized linear regression model
GeneralizedLinearModel.stepwiseCreate generalized linear regression model by stepwise regression
GeneralizedParetoDistributionGeneralized Pareto probability distribution object
geocdfGeometric cumulative distribution function
geoinvGeometric inverse cumulative distribution function
geomeanGeometric mean
geopdfGeometric probability density function
georndGeometric random numbers
geostatGeometric mean and variance
getlabelsAccess categorical array labels
getlevelsAccess categorical array levels
gevcdfGeneralized extreme value cumulative distribution function
gevfitGeneralized extreme value parameter estimates
gevinvGeneralized extreme value inverse cumulative distribution function
gevlikeGeneralized extreme value negative log-likelihood
gevpdfGeneralized extreme value probability density function
gevrndGeneralized extreme value random numbers
gevstatGeneralized extreme value mean and variance
glineInteractively add line to plot
glmfitGeneralized linear model regression
glmvalGeneralized linear model values
glyphplotGlyph plot
gmdistributionConstruct Gaussian mixture distribution
gmdistribution.fitGaussian mixture parameter estimates
gnameAdd case names to plot
gpcdfGeneralized Pareto cumulative distribution function
gpfitGeneralized Pareto parameter estimates
gpinvGeneralized Pareto inverse cumulative distribution function
gplikeGeneralized Pareto negative log-likelihood
gplotmatrixMatrix of scatter plots by group
gppdfGeneralized Pareto probability density function
gprndGeneralized Pareto random numbers
gpstatGeneralized Pareto mean and variance
grp2idxCreate index vector from grouping variable
grpstatsSummary statistics organized by group
grpstatsCompute descriptive statistics of repeated measures data by group
gscatterScatter plot by group
HalfNormalDistributionHalf-normal probability distribution object
haltonsetConstruct Halton quasi-random point set
HamiltonianSamplerHamiltonian Monte Carlo (HMC) sampler
HamiltonianSampler.diagnosticsMarkov Chain Monte Carlo diagnostics
HamiltonianSampler.drawSamplesGenerate Markov chain using Hamiltonian Monte Carlo (HMC)
HamiltonianSampler.estimateMAPEstimate maximum of log probability density
HamiltonianSampler.tuneSampler Tune Hamiltonian Monte Carlo (HMC) sampler
harmmeanHarmonic mean
hist3Bivariate histogram
histfitHistogram with a distribution fit
hmcSamplerHamiltonian Monte Carlo (HMC) sampler
hmmdecodeHidden Markov model posterior state probabilities
hmmestimateHidden Markov model parameter estimates from emissions and states
hmmgenerateHidden Markov model states and emissions
hmmtrainHidden Markov model parameter estimates from emissions
hmmviterbiHidden Markov model most probable state path
hougenHougen-Watson model
hygecdfHypergeometric cumulative distribution function
hygeinvHypergeometric inverse cumulative distribution function
hygepdfHypergeometric probability density function
hygerndHypergeometric random numbers
hygestatHypergeometric mean and variance
hyperparametersVariable descriptions for optimizing a fit function
icdfInverse cumulative distribution functions
inconsistentInconsistency coefficient
increaseBIncrease reference data sets
interactionplotInteraction plot for grouped data
InverseGaussianDistributionInverse Gaussian probability distribution object
invpredInverse prediction
iqrInterquartile range
islevelDetermine if levels are in nominal or ordinal array
ismissingFind dataset array elements with missing values
iwishrndInverse Wishart random numbers
jackknifeJackknife sampling
jbtestJarque-Bera test
johnsrndJohnson system random numbers
joinMerge observations
KDTreeSearcherNearest neighbor search using Kd-tree
KDTreeSearcherGrow Kd-tree
KernelDistributionKernel probability distribution object
kfoldEdgeClassification edge for observations not used for training
kfoldEdgeClassification edge for observations not used for training
kfoldEdgeClassification edge for observations not used for training
kfoldEdgeClassification edge for observations not used for training
kfoldEdgeClassification edge for observations not used for training
kfoldfunCross validate function
kfoldfunCross validate function
kfoldfunCross validate function
kfoldLossCross-validation loss of partitioned regression model
kfoldLossClassification loss for observations not used for training
kfoldLossClassification loss for observations not used for training
kfoldLossClassification loss for observations not used in training
kfoldLossClassification loss for observations not used in training
kfoldLossClassification loss for observations not used for training
kfoldMarginClassification margins for observations not used for training
kfoldMarginClassification margins for observations not used for training
kfoldMarginClassification margins for observations not used in training
kfoldMarginClassification margins for observations not used in training
kfoldPredictPredict response for observations not used for training.
kfoldPredictPredict response for observations not used for training
kfoldPredictPredict responses for observations not used for training
kfoldPredictPredict labels for observations not used for training
kfoldPredictPredict labels for observations not used for training
kmeansk-means clustering
kmedoidsk-medoids clustering
knnsearchk-nearest neighbor search using Kd-tree or exhaustive search
kruskalwallisKruskal-Wallis test
ksdensityKernel smoothing function estimate for univariate and bivariate data
kstestOne-sample Kolmogorov-Smirnov test
kstest2Two-sample Kolmogorov-Smirnov test
kurtosisKurtosis
lassoRegularized least-squares regression using lasso or elastic net algorithms
lassoglmLasso or elastic net regularization for generalized linear model regression
lassoPlotTrace plot of lasso fit
levelcountsElement counts by level of a nominal or ordinal array
leverageLeverage
lhsdesignLatin hypercube sample
lhsnormLatin hypercube sample from normal distribution
lillietestLilliefors test
LinearMixedModel Linear mixed-effects model class
LinearMixedModel.fitFit linear mixed-effects model using tables
LinearMixedModel.fitmatrix Fit linear mixed-effects model using design matrices
LinearModelLinear regression model class
LinearModel.fitCreate linear regression model
LinearModel.stepwiseCreate linear regression model by stepwise regression
linhyptestLinear hypothesis test
linkageAgglomerative hierarchical cluster tree
loadCompactModelReconstruct model object from saved model for code generation
LogisticDistributionLogistic probability distribution object
LoglogisticDistributionLoglogistic probability distribution object
logncdfLognormal cumulative distribution function
lognfitLognormal parameter estimates
logninvLognormal inverse cumulative distribution function
lognlikeLognormal negative log-likelihood
LognormalDistributionLognormal probability distribution object
lognpdfLognormal probability density function
lognrndLognormal random numbers
lognstatLognormal mean and variance
logPLog unconditional probability density for discriminant analysis classifier
logPLog unconditional probability density for naive Bayes classifier
lossRegression error for support vector machine regression model
lossRegression error for Gaussian process regression model
lossRegression error
lossRegression error
lossClassification error
lossClassification error
lossClassification error for naive Bayes classifier
lossLoss of k-nearest neighbor classifier
lossClassification loss for multiclass, error-correcting output codes model
lossClassification loss for linear classification models
lossClassification error for support vector machine classifiers
lossClassification loss for Gaussian kernel classification model
lossClassification error
loss Evaluate accuracy of learned feature weights on test data
lossEvaluate accuracy of learned feature weights on test data
lslineAdd least-squares line to scatter plot
madMean or median absolute deviation
mahalMahalanobis distance
mahalMahalanobis distance to class means
maineffectsplotMain effects plot for grouped data
makedistCreate probability distribution object
manovaMultivariate analysis of variance
manova1One-way multivariate analysis of variance
manovaclusterDendrogram of group mean clusters following MANOVA
marginClassification margins
marginClassification margins
marginClassification margins for naive Bayes classifiers
marginMargin of k-nearest neighbor classifier
marginClassification margins for support vector machine classifiers
marginClassification margins for multiclass, error-correcting output codes model
marginClassification margins for linear classification models
marginClassification margins for Gaussian kernel classification model
marginClassification margins
margmean Estimate marginal means
mat2datasetConvert matrix to dataset array
mauchlyMauchly’s test for sphericity
mdscaleNonclassical multidimensional scaling
meanMean of probability distribution
medianMedian of probability distribution
mergelevelsMerge levels of nominal or ordinal arrays
mhsampleMetropolis-Hastings sample
mleMaximum likelihood estimates
mlecovAsymptotic covariance of maximum likelihood estimators
mnpdfMultinomial probability density function
mnrfitMultinomial logistic regression
mnrndMultinomial random numbers
mnrvalMultinomial logistic regression values
momentCentral moments
multcompareMultiple comparison test
multcompareMultiple comparison of estimated marginal means
MultinomialDistributionMultinomial probability distribution object
multivarichartMultivari chart for grouped data
mvksdensityKernel smoothing function estimate for multivariate data
mvncdfMultivariate normal cumulative distribution function
mvnpdfMultivariate normal probability density function
mvnrndMultivariate normal random numbers
mvregressMultivariate linear regression
mvregresslikeNegative log-likelihood for multivariate regression
mvtcdfMultivariate t cumulative distribution function
mvtpdfMultivariate t probability density function
mvtrndMultivariate t random numbers
NakagamiDistributionNakagami probability distribution object
nancovCovariance ignoring NaN values
nanmaxMaximum ignoring NaN values
nanmeanMean ignoring NaN values
nanmedianMedian ignoring NaN values
nanminMinimum ignoring NaN values
nanstdStandard deviation ignoring NaN values
nansumSum ignoring NaN values
nanvarVariance, ignoring NaN values
nbincdfNegative binomial cumulative distribution function
nbinfitNegative binomial parameter estimates
nbininvNegative binomial inverse cumulative distribution function
nbinpdfNegative binomial probability density function
nbinrndNegative binomial random numbers
nbinstatNegative binomial mean and variance
ncfcdfNoncentral F cumulative distribution function
ncfinvNoncentral F inverse cumulative distribution function
ncfpdfNoncentral F probability density function
ncfrndNoncentral F random numbers
ncfstatNoncentral F mean and variance
nctcdfNoncentral t cumulative distribution function
nctinvNoncentral t inverse cumulative distribution function
nctpdfNoncentral t probability density function
nctrndNoncentral t random numbers
nctstatNoncentral t mean and variance
ncx2cdfNoncentral chi-square cumulative distribution function
ncx2invNoncentral chi-square inverse cumulative distribution function
ncx2pdfNoncentral chi-square probability density function
ncx2rndNoncentral chi-square random numbers
ncx2statNoncentral chi-square mean and variance
NegativeBinomialDistributionNegative binomial distribution object
negloglikNegative log likelihood of probability distribution
nLinearCoeffsNumber of nonzero linear coefficients
nlinfitNonlinear regression
nlintoolInteractive nonlinear regression
nlmefitNonlinear mixed-effects estimation
nlmefitsaFit nonlinear mixed-effects model with stochastic EM algorithm
nlparciNonlinear regression parameter confidence intervals
nlpredciNonlinear regression prediction confidence intervals
nnmfNonnegative matrix factorization
nominalCreate nominal array
nominalArrays for nominal data
NonLinearModelNonlinear regression model class
NonLinearModel.fitFit nonlinear regression model
NormalDistributionNormal probability distribution object
normcdfNormal cumulative distribution function
normfitNormal parameter estimates
norminvNormal inverse cumulative distribution function
normlikeNormal negative log-likelihood
normpdfNormal probability density function
normplotNormal probability plot
normrndNormal random numbers
normspecNormal density plot between specifications
normstatNormal mean and variance
oobEdgeOut-of-bag classification edge
oobLossOut-of-bag classification error
oobMarginOut-of-bag classification margins
oobPermutedPredictorImportancePredictor importance estimates by permutation of out-of-bag predictor observations for random forest of regression trees
oobPermutedPredictorImportancePredictor importance estimates by permutation of out-of-bag predictor observations for random forest of classification trees
oobPredictPredict out-of-bag response of ensemble
oobPredictEnsemble predictions for out-of-bag observations
oobPredictPredict out-of-bag response of ensemble
oobQuantileErrorOut-of-bag quantile loss of bag of regression trees
oobQuantilePredictQuantile predictions for out-of-bag observations from bag of regression trees
optimalleaforderOptimal leaf ordering for hierarchical clustering
optimizableVariableVariable description for bayesopt or other optimizers
ordinalCreate ordinal array
ordinalArrays for ordinal data
parallelcoordsParallel coordinates plot
paramciConfidence intervals for probability distribution parameters
paretotailsConstruct Pareto tails object
partialcorrLinear or rank partial correlation coefficients
partialcorriPartial correlation coefficients adjusted for internal variables
pcaPrincipal component analysis of raw data
pcacovPrincipal component analysis on covariance matrix
pcaresResiduals from principal component analysis
pdfProbability density functions
pdfProbability density function for Gaussian mixture distribution
pdistPairwise distance between pairs of observations
pdist2Pairwise distance between two sets of observations
pearsrndPearson system random numbers
perfcurveReceiver operating characteristic (ROC) curve or other performance curve for classifier output
PiecewiseLinearDistributionPiecewise linear probability distribution object
plot Plot clustering evaluation object criterion values
plotPlot data with optional grouping
plotScatter plot or added variable plot of linear model
plotPlot Bayesian optimization results
plotAddedAdded variable plot or leverage plot for linear model
plotAdjustedResponseAdjusted response plot for linear regression model
plotDiagnosticsPlot diagnostics of linear regression model
plotDiagnosticsPlot diagnostics of generalized linear regression model
plotDiagnosticsPlot diagnostics of nonlinear regression model
plotEffectsPlot main effects of each predictor in linear regression model
plotInteractionPlot interaction effects of two predictors in linear regression model
plotPartialDependenceCreate partial dependence plot (PDP) and individual conditional expectation (ICE) plots
plotprofile Plot expected marginal means with optional grouping
plotResidualsPlot residuals of linear mixed-effects model
plotResidualsPlot residuals of generalized linear mixed-effects model
plotResidualsPlot residuals of linear regression model
plotResidualsPlot residuals of generalized linear regression model
plotResidualsPlot residuals of nonlinear regression model
plotSlicePlot of slices through fitted linear regression surface
plotSlicePlot of slices through fitted generalized linear regression surface
plotSlicePlot of slices through fitted nonlinear regression surface
plsregressPartial least-squares regression
poisscdfPoisson cumulative distribution function
poissfitPoisson parameter estimates
poissinvPoisson inverse cumulative distribution function
PoissonDistributionPoisson probability distribution object
poisspdfPoisson probability density function
poissrndPoisson random numbers
poisstatPoisson mean and variance
polyconfPolynomial confidence intervals
polytoolInteractive polynomial fitting
posteriorPosterior probabilities of components
postFitStatisticsCompute post-fit statistics for the exact Gaussian process regression model
ppcaProbabilistic principal component analysis
prctilePercentiles of a data set
predictCompute predicted values given predictor values
predictPredict response of linear regression model
predictPredict response of linear regression model
predict Predict response of linear mixed-effects model
predictPredict response of generalized linear regression model
predictPredict labels for linear classification models
predictPredict labels for Gaussian kernel classification model
predictPredict response of generalized linear mixed-effects model
predictPredict response of nonlinear regression model
predictPredict responses using support vector machine regression model
predictPredict response of Gaussian process regression model
predictPredict responses using regression tree
predictPredict responses using ensemble of regression models
predictPredict responses using ensemble of bagged decision trees
predictPredict labels using classification tree
predictPredict labels using discriminant analysis classification model
predictPredict labels using naive Bayes classification model
predictPredict labels using k-nearest neighbor classification model
predictPredict labels using support vector machine classification model
predictPredict labels using multiclass, error-correcting output codes model
predictPredict labels using ensemble of classification models
predictPredict responses using neighborhood component analysis (NCA) regression model
predictPredict responses using neighborhood component analysis (NCA) classifier
predictConstraintsPredict coupled constraint violations at a set of points
predictErrorPredict error value at a set of points
predictObjectivePredict objective function at a set of points
predictObjectiveEvaluationTimePredict objective function run times at a set of points
predictorImportanceEstimates of predictor importance
predictorImportanceEstimates of predictor importance
predictorImportanceEstimates of predictor importance
predictorImportanceEstimates of predictor importance
princompPrincipal component analysis (PCA) on data
Probability Distribution FunctionInteractive density and distribution plots
ProbDistUnivKernelConstruct ProbDistUnivKernel object
ProbDistUnivParamObject representing univariate parametric probability distribution
probplotProbability plots
procrustesProcrustes analysis
proflikProfile likelihood function for probability distribution
pruneProduce sequence of subtrees by pruning
pruneProduce sequence of subtrees by pruning
qqplotQuantile-quantile plot
qrandsetAbstract quasi-random point set class
qrandstreamConstruct quasi-random number stream
quantileQuantiles of a data set
quantileErrorQuantile loss using bag of regression trees
quantilePredictPredict response quantile using bag of regression trees
randgGamma random numbers with unit scale
randomRandom numbers
randomRandom numbers from Gaussian mixture distribution
random Generate new random response values given predictor values
randomSimulate responses for linear regression model
random Generate random responses from fitted linear mixed-effects model
randomSimulate responses for generalized linear regression model
randomGenerate random responses from fitted generalized linear mixed-effects model
randomSimulate responses for nonlinear regression model
randomEffects Estimates of random effects and related statistics
randomEffectsEstimates of random effects and related statistics
randsampleRandom sample
randtoolInteractive random number generation
rangeRange of values
rangesearchFind all neighbors within specified distance using exhaustive search or Kd-tree
ranksumWilcoxon rank sum test
ranovaRepeated measures analysis of variance
raylcdfRayleigh cumulative distribution function
RayleighDistributionRayleigh probability distribution object
raylfitRayleigh parameter estimates
raylinvRayleigh inverse cumulative distribution function
raylpdfRayleigh probability density function
raylrndRayleigh random numbers
raylstatRayleigh mean and variance
rcoplotResidual case order plot
ReconstructionICAFeature extraction by reconstruction ICA
refcurveAdd reference curve to plot
refit Refit generalized linear mixed-effects model
refitRefit neighborhood component analysis (NCA) model for regression
refitRefit neighborhood component analysis (NCA) model for classification
reflineAdd reference line to plot
regressMultiple linear regression
RegressionBaggedEnsembleRegression ensemble grown by resampling
RegressionEnsembleEnsemble regression
RegressionEnsemble.compactCreate compact regression ensemble
RegressionEnsemble.regularizeFind weights to minimize resubstitution error plus penalty term
RegressionEnsemble.resubLossRegression error by resubstitution
RegressionEnsemble.resubPredictPredict response of ensemble by resubstitution
RegressionEnsemble.shrinkPrune ensemble
RegressionGPGaussian process regression model class
RegressionLinearLinear regression model for high-dimensional data
RegressionPartitionedEnsembleCross-validated regression ensemble
RegressionPartitionedLinearCross-validated linear regression model for high-dimensional data
RegressionPartitionedModelCross-validated regression model
RegressionSVMSupport vector machine regression model
RegressionTreeRegression tree
regstatsRegression diagnostics
relieffImportance of attributes (predictors) using ReliefF algorithm
removeLearnersRemove members of compact classification ensemble
removeTermsRemove terms from linear model
removeTermsRemove terms from generalized linear model
repartitionRepartition data for cross-validation
RepeatedMeasuresModelRepeated measures model class
residualsResiduals of fitted linear mixed-effects model
residualsResiduals of fitted generalized linear mixed-effects model
responseResponse vector of the linear mixed-effects model
responseResponse vector of generalized linear mixed-effects model
resubEdgeClassification edge by resubstitution
resubEdgeClassification edge by resubstitution
resubEdgeClassification edge for naive Bayes classifiers by resubstitution
resubEdgeEdge of k-nearest neighbor classifier by resubstitution
resubEdgeClassification edge for support vector machine classifiers by resubstitution
resubEdgeClassification edge by resubstitution for multiclass, error-correcting output codes model
resubEdgeClassification edge by resubstitution
resubLossResubstitution loss for support vector machine regression model
resubLossResubstitution loss for a trained Gaussian process regression model
resubLossRegression error by resubstitution
resubLossClassification error by resubstitution
resubLossClassification error by resubstitution
resubLossClassification loss for naive Bayes classifiers by resubstitution
resubLossLoss of k-nearest neighbor classifier by resubstitution
resubLossClassification loss for support vector machine classifiers by resubstitution
resubLossClassification loss by resubstitution for multiclass, error-correcting output codes model
resubLossClassification error by resubstitution
resubMarginClassification margins by resubstitution
resubMarginClassification margins by resubstitution
resubMarginClassification margins for naive Bayes classifiers by resubstitution
resubMarginMargin of k-nearest neighbor classifier by resubstitution
resubMarginClassification margins for support vector machine classifiers by resubstitution
resubMarginClassification margins by resubstitution for multiclass, error-correcting output codes model
resubMarginClassification margins by resubstitution
resubPredictPredict resubstitution response of support vector machine regression model
resubPredictResubstitution prediction from a trained Gaussian process regression model
resubPredictPredict resubstitution response of tree
resubPredictPredict resubstitution response of tree
resubPredictPredict resubstitution response of classifier
resubPredictPredict naive Bayes classifier resubstitution response
resubPredictPredict resubstitution response of k-nearest neighbor classifier
resubPredictPredict support vector machine classifier resubstitution responses
resubPredictPredict resubstitution responses for multiclass, error-correcting output codes model
resubPredictPredict ensemble response by resubstitution
resumeResume training support vector machine regression model
resumeResume training ensemble
resumeResume training support vector machine classifier
resumeResume training of Gaussian kernel classification model
resumeResume training ensemble
resumeResume a Bayesian optimization
ricaFeature extraction by using reconstruction ICA
RicianDistributionRician probability distribution object
ridgeRidge regression
robustcovRobust multivariate covariance and mean estimate
robustdemoInteractive robust regression
robustfitRobust regression
rotatefactorsRotate factor loadings
rowexchRow exchange
rsmdemoInteractive response surface demonstration
rstoolInteractive response surface modeling
runstestRun test for randomness
sampsizepwrSample size and power of test
saveCompactModelSave model object in file for code generation
scatterhistScatter plot with marginal histograms
selectModelsChoose subset of regularized linear classification models
selectModelsChoose subset of regularized, binary linear classification models
sequentialfsSequential feature selection
setlabelsAssign labels to levels of nominal or ordinal arrays
signrankWilcoxon signed rank test
signtestSign test
silhouetteSilhouette plot
SilhouetteEvaluationSilhouette criterion clustering evaluation object
skewnessSkewness
slicesampleSlice sampler
sobolsetConstruct Sobol quasi-random point set
sparsefiltFeature extraction by using sparse filtering
SparseFilteringFeature extraction by sparse filtering
squareformFormat distance matrix
StableDistributionStable probability distribution object
statgetAccess values in statistics options structure
statsetCreate statistics options structure
stdStandard deviation of probability distribution
stepImprove linear regression model by adding or removing terms
stepImprove generalized linear regression model by adding or removing terms
stepwiseInteractive stepwise regression
stepwisefitStepwise regression
stepwiseglmCreate generalized linear regression model by stepwise regression
stepwiselm Create linear regression model using stepwise regression
struct2datasetConvert structure array to dataset array
surfhtInteractive contour plot
surrogateAssociationMean predictive measure of association for surrogate splits in decision tree
svmclassifyClassify using support vector machine (SVM)
svmtrainTrain support vector machine classifier
table2datasetConvert table to dataset array
tabulateFrequency table
tblreadRead tabular data from file
tblwriteWrite tabular data to file
tcdfStudent's t cumulative distribution function
tdfreadRead tab-delimited file
templateDiscriminantDiscriminant analysis classifier template
templateECOCError-correcting output codes learner template
templateEnsembleEnsemble learning template
templateKNNk-nearest neighbor classifier template
templateLinearLinear classification learner template
templateNaiveBayesNaive Bayes classifier template
templateSVMSupport vector machine template
templateTreeCreate decision tree template
testTest indices for cross-validation
testcholdoutCompare predictive accuracies of two classification models
testckfoldCompare accuracies of two classification models by repeated cross validation
tiedrankRank adjusted for ties
tinvStudent's t inverse cumulative distribution function
tLocationScaleDistributiont Location-Scale probability distribution object
tpdfStudent's t probability density function
trainingTraining indices for cross-validation
transformTransform predictors into extracted features
TreeBaggerCreate bag of decision trees
TreeBaggerBag of decision trees
TreeBagger.appendAppend new trees to ensemble
TreeBagger.compactCompact ensemble of decision trees
TreeBagger.errorError (misclassification probability or MSE)
TreeBagger.fillproxProximity matrix for training data
TreeBagger.growTreesTrain additional trees and add to ensemble
TreeBagger.marginClassification margin
TreeBagger.mdsproxMultidimensional scaling of proximity matrix
TreeBagger.meanMarginMean classification margin
TreeBagger.oobErrorOut-of-bag error
TreeBagger.oobMarginOut-of-bag margins
TreeBagger.oobMeanMarginOut-of-bag mean margins
TriangularDistributionTriangular probability distribution object
trimmeanMean excluding outliers
trndStudent's t random numbers
truncateTruncate probability distribution object
tsnet-Distributed Stochastic Neighbor Embedding
tstatStudent's t mean and variance
ttestOne-sample and paired-sample t-test
ttest2Two-sample t-test
unidcdfDiscrete uniform cumulative distribution function
unidinvDiscrete uniform inverse cumulative distribution function
unidpdfDiscrete uniform probability density function
unidrndDiscrete uniform random numbers
unidstatDiscrete uniform mean and variance
unifcdfContinuous uniform cumulative distribution function
unifinvContinuous uniform inverse cumulative distribution function
unifitContinuous uniform parameter estimates
UniformDistributionUniform probability distribution object
unifpdfContinuous uniform probability density function
unifrndContinuous uniform random numbers
unifstatContinuous uniform mean and variance
varVariance of probability distribution
vartestChi-square variance test
vartest2Two-sample F-test for equal variances
vartestn Multiple-sample tests for equal variances
viewView tree
viewView tree
wblcdfWeibull cumulative distribution function
wblfitWeibull parameter estimates
wblinvWeibull inverse cumulative distribution function
wbllikeWeibull negative log-likelihood
wblpdfWeibull probability density function
wblplotWeibull probability plot
wblrndWeibull random numbers
wblstatWeibull mean and variance
WeibullDistributionWeibull probability distribution object
wishrndWishart random numbers
x2fxConvert predictor matrix to design matrix
xlsreadRead Microsoft Excel spreadsheet file
xptreadCreate table from data stored in SAS XPORT format file
zscoreStandardized z-scores
ztestz-test
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