A Matlab toolbox for pattern recognition Imported pages from 37Steps

Home   Guide   Software   Glossary   FAQ   Blog   About


Linear and Quadratic Classifiers

fishercMinimum least square linear classifier
ldcNormal densities based linear (muli-class) classifier
loglcLogistic linear classifier
nmcNearest mean linear classifier
nmscScaled nearest mean linear classifier
qdcNormal densities based quadratic (multi-class) classifier
udcUncorrelated normal densities based quadratic classifier

Other Classifiers

nbayescBayes classifier for given normal densities
mogcMixture of gaussians classification
knnck-nearest neighbour classifier (find k, build classifier)
parzencParzen classifier
parzendcParzen density based classifier
weakcWeak classifier
stumpcDecision stump classifier
adaboostcADABoost classifier
treecConstruct binary decision tree classifier
dtcDecision tree classifier, rewritten, also for nominal features
randomforestcBreiman’s random forest classifier
naivebcNaive Bayes classifier
fdscFeature based dissimilarity space classifier
drbmc,Discriminative restricted Boltzmann machine classifier

Support Vector Classifiers

libsvcSupport vector classifier by LIBSVM
nulibsvcSupport vector classifier by LIBSVM
rblibsvcRadial basis SV classifier by LIBSVM
svcSupport vector classifier
nusvcSupport vector classifier
rbsvcRadial basis SV classifier

Perceptrons and Neural Network based Classifiers

bpxncFeed forward neural network classifier by backpropagation
lmncFeed forward neural network by Levenberg-Marquardt rule
neurcAutomatic neural network classifier
perlcLinear perceptron
rbncRadial basis neural network classifier
rnncRandom neural network classifier
vpcVoted perceptron classifier

Various related Routines

distmahaMahalanobis distance
meancovEstimation of means and covariance matrices from multiclass data
ediconEdit and condense training sets
testkError estimation for k-nearest neighbour rule
testpError estimation for Parzen classifier
testnError estimate of discriminant on normal distributions
testcGeneral error estimation routine for trained classifiers
classcConverts a mapping into a classifier
labeldFind labels of objects by classification
rejectcCreates reject version of exisiting classifier