classim | Classify image using a given classifier | more routines |
classc | Convert mapping to classifier | |
labeld | Find labels of objects by classification | |
cleval | Classifier evaluation (learning curve) | |
clevalb | Classifier evaluation (learning curve), bootstrap version | |
clevalf | Classifier evaluation (feature size curve) | |
clevals | Classifier evaluation (feature /learning curve), bootstrap | |
confmat | Computation of confusion matrix | |
costm | Cost mapping, classification using costs | |
prcrossval | Crossvalidation | |
disperror | Display error matrix with information on classifiers and datasets | |
labelim | Construct image of labeled pixels | |
loso | Leave_one_set_out crossvalidation | |
mclassc | Computation of multi-class classifier from 2-class discriminants | |
reject | Compute error-reject trade-off curve | |
prroc | Receiver-operator curve (ROC) | |
shiftop | Shift operating point of classifier | |
testc | General error estimation routine for trained classifiers | |
testd | Error of dataset applied to given classifier | |
testauc | Estimate 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.