| name |
description |
note |
| linear methods
|
| affine |
Linear feature extraction |
|
| fisherm |
Fisher's linear mapping |
|
| fisherc |
Fisher's linear classifier |
|
| ldc |
Linear Bayes Normal Classifier |
|
| loglc |
Logistic linear classifier |
|
| nmc |
Nearest Mean Classifier |
|
| nmsc |
Nearest Mean Scaled Classifier mapping |
|
| pca |
Principal Component Analysis mapping |
|
| pcaklm |
Affine Karhunen-Loeve mapping |
|
| pcldc |
Linear classifier using PC expansion on the joint data |
|
| perlc |
Linear Perceptron classifier |
|
| parametric |
| gaussm |
Mixture of Gaussians density estimate |
|
| mogc |
Mixture of Gaussian classifier |
|
| normal_map |
Normal-density mappings |
|
| qdc |
Quadratic Bayes classifier |
|
| udc |
Uncorrelated normal based quadratic Bayes classifier |
|
| non-parametric |
| knnc |
k-nearest neighbour classifier |
|
| parzenc |
Parzen classifier |
only scalar smoothing |
| parzendc |
Parzen density based classifier |
only scalar smoothing |
| parzenm |
Parzen density estimation |
only scalar smoothing |
| treec |
Decision tree |
|
| stumpc |
Decision stump |
|
| Support Vector Machines |
| nusvc |
Support Vector Classifier: NU algorithm |
|
| rbsvc |
Radial basis Support Vector Classifier |
|
| svc |
Support Vector Classifier |
|
| proximities, kernels |
| distm |
Square Euclidean distance |
|
| proxm |
Proximity mapping |
polynomial, RBF, Eucl, sq.Eucl. |
| combining strategies |
| parallel |
Parallel combining classifiers |
|
| sequential |
Sequential combining classifiers |
|
| stacked |
Stacked combining classifiers |
|
| sigm |
Sigmoid mapping of classifier outputs |
|
| classc |
Classifier output normalization |
|
| feature selection |
| cmapm |
Data-independent mappings |
only feature selection |
| featsel |
Feature Selection |
|
