Classifiers
Linear and Quadratic Classifiers
| fisherc | Minimum least square linear classifier | |
| ldc | Normal densities based linear (muli-class) classifier | |
| loglc | Logistic linear classifier | |
| nmc | Nearest mean linear classifier | |
| nmsc | Scaled nearest mean linear classifier | |
| qdc | Normal densities based quadratic (multi-class) classifier | |
| udc | Uncorrelated normal densities based quadratic classifier |
Other Classifiers
| nbayesc | Bayes classifier for given normal densities | |
| mogc | Mixture of gaussians classification | |
| knnc | k-nearest neighbour classifier (find k, build classifier) | |
| parzenc | Parzen classifier | |
| parzendc | Parzen density based classifier | |
| weakc | Weak classifier | |
| stumpc | Decision stump classifier | |
| adaboostc | ADABoost classifier | |
| treec | Construct binary decision tree classifier | |
| dtc | Decision tree classifier, rewritten, also for nominal features | |
| randomforestc | Breiman’s random forest classifier | |
| naivebc | Naive Bayes classifier | |
| fdsc | Feature based dissimilarity space classifier | |
| drbmc, | Discriminative restricted Boltzmann machine classifier |
Support Vector Classifiers
| libsvc | Support vector classifier by LIBSVM | |
| nulibsvc | Support vector classifier by LIBSVM | |
| rblibsvc | Radial basis SV classifier by LIBSVM | |
| svc | Support vector classifier | |
| nusvc | Support vector classifier | |
| rbsvc | Radial basis SV classifier |
Perceptrons and Neural Network based Classifiers
| bpxnc | Feed forward neural network classifier by backpropagation | |
| lmnc | Feed forward neural network by Levenberg-Marquardt rule | |
| neurc | Automatic neural network classifier | |
| perlc | Linear perceptron | |
| rbnc | Radial basis neural network classifier | |
| rnnc | Random neural network classifier | |
| vpc | Voted perceptron classifier |
Various related Routines
| distmaha | Mahalanobis distance | |
| meancov | Estimation of means and covariance matrices from multiclass data | |
| edicon | Edit and condense training sets | |
| testk | Error estimation for k-nearest neighbour rule | |
| testp | Error estimation for Parzen classifier | |
| testn | Error estimate of discriminant on normal distributions | |
| testc | General error estimation routine for trained classifiers | |
| classc | Converts a mapping into a classifier | |
| labeld | Find labels of objects by classification | |
| rejectc | Creates reject version of exisiting classifier |
