A Matlab toolbox for pattern recognition Imported pages from 37Steps

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Evaluation – Test Routines

classimClassify image using a given classifiermore routines
classcConvert mapping to classifier
labeldFind labels of objects by classification
clevalClassifier evaluation (learning curve)
clevalbClassifier evaluation (learning curve), bootstrap version
clevalfClassifier evaluation (feature size curve)
clevalsClassifier evaluation (feature /learning curve), bootstrap
confmatComputation of confusion matrix
costmCost mapping, classification using costs
disperrorDisplay error matrix with information on classifiers and datasets
labelimConstruct image of labeled pixels
losoLeave_one_set_out crossvalidation
mclasscComputation of multi-class classifier from 2-class discriminants
rejectCompute error-reject trade-off curve
prrocReceiver-operator curve (ROC)
shiftopShift operating point of classifier
testcGeneral error estimation routine for trained classifiers
testdError of dataset applied to given classifier
testaucEstimate error as area under the ROC

elements: datasets datafiles cells and doubles mappings classifiers mapping types.
operations:datasets datafiles cells and doubles mappings classifiers stacked parallel sequential dyadic.
user commands:datasets representation classifiers evaluation clustering examples support routines.
introductory examples:IntroductionScatterplotsDatasets Datafiles Mappings Classifiers Evaluation Learning curves Feature curves Dimension reductionCombining classifiers Dissimilarities.
advanced examples.