# 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 |