| constant | Constant Classifier |
| constantModel | Combine Model-based Recursive Partitioning with a Constant... |
| dalda | Discriminant Adaptive Linear Discriminant Analysis |
| dalr | Discriminant Adaptive Logistic Regression |
| damultinom | Discriminant Adaptive Multinomial Log-linear Models |
| dannet | Discriminant Adaptive Neural Network |
| daqda | Discriminant Adaptive Quadratic Discriminant Analysis |
| dasvm | Discriminant Adaptive Support Vector Machine |
| FLXMCL | Class "FLXMCL" |
| FLXMCLconstant | Mixtures of Constant Classifiers |
| FLXMCLlda | Mixtures of Linear Discriminant Analysis Models |
| FLXMCLmultinom | Mixtures of Multinomial Regression Models |
| FLXMCLnnet | Mixtures of Neural Networks |
| FLXMCLqda | Mixtures of Quadratic Discriminant Analysis Models |
| FLXMCLsvm | Mixtures of Support Vector Machines |
| FLXPwlda | Creator Function for the Concomitant Variable Model based on... |
| FLXPwlda-class | Class "FLXPwlda" |
| kda | Kernel Classification Rules |
| kmc | K-Means Classification |
| ldaModel | Combine Model-based Recursive Partitioning with Linear... |
| multinomModel | Combine Model-based Recursive Partitioning with Multinomial... |
| myfitted | Extract Fitted Values |
| mypredict | Predict Values |
| nnetGradient | Calculate value of objective function and gradient for a... |
| nnetModel | Combine Model-based Recursive Partitioning with Neural... |
| oslda | Observation Specific Linear Discriminant Analysis |
| osmultinom | Observation Specific Multinomial Log-linear Models |
| osnnet | Observation Specific Neural Networks |
| osqda | Observation Specific Quadratic Discriminant Analysis |
| ossvm | Observation Specific Support Vector Machines |
| predict.constant | Classify Multivariate Observations Based on the Constant... |
| predict.dalda | Classify Multivariate Observations Based on Discriminant... |
| predict.dalr | Classify Multivariate Observations Based on Discriminant... |
| predict.damultinom | Predict New Examples by a Trained Discriminant Adaptive... |
| predict.dannet | Predict New Examples by a Trained Discriminant Adaptive... |
| predict.daqda | Classify Multivariate Observations Based on Discriminant... |
| predict.dasvm | Predict Method for Discriminant Adaptive Support Vector... |
| predict.kda | Classify Multivariate Observations Based on Kernel Rules |
| predict.kmc | K-means Classification |
| predict.oslda | Classify Multivariate Observations Based on Observation... |
| predict.osmultinom | Predict New Examples Based on Observation Specific... |
| predict.osnnet | Predict New Examples Based on Observation Specific Neural... |
| predict.osqda | Classify Multivariate Observations Based on Observation... |
| predict.ossvm | Predict New Observations with Observation Specific Support... |
| predict.wlda | Classify Multivariate Observations Based on Weighted Linear... |
| predict.wqda | Classify Multivariate Observations Based on Weighted... |
| predict.wsvm | Predict New Examples by a Trained (Weighted) Support Vector... |
| qdaModel | Combine Model-based Recursive Partitioning with Quadratic... |
| svmModel | Combine Model-based Recursive Partitioning with Support... |
| wfs | Generation of Window Functions |
| wlda | Weighted Linear Discriminant Analysis |
| wqda | Weighted Quadratic Discriminant Analysis |
| wsvm | Weighted Support Vector Machines |
