Overview | Package | Class | Use | Tree | Deprecated | Index | Help
PREV NEXT | FRAMES NO FRAMES

## Uses of Class
fr.lip6.type.TrainingSample

Packages that use TrainingSample
fr.lip6.classifier |
fr.lip6.kernel | Package containing generic kernels on vectors.
fr.lip6.kernel.adaptative |

Uses of TrainingSample in fr.lip6.classifier

Methods in fr.lip6.classifier that return types with arguments of type TrainingSample
`java.util.ArrayList<TrainingSample<T>>` | `SMOSVM.getTrainingSet()` the ArrayList of TrainingSample used for training

Methods in fr.lip6.classifier with parameters of type TrainingSample
`void` | `DoublePegasosSVM.train(TrainingSample<double[]> t)`
`void` | `SMOSVM.train(TrainingSample<T> t)`
`void` | `EnhancedSMOSVM.train(TrainingSample<T> t)`
`void` | `SimpleMKL.train(TrainingSample<T> train)`
`void` | `PegasosSVM.train(TrainingSample<T> t)`
`void` | `ParzenClassifier.train(TrainingSample<T> t)`
`void` | `Classifier.train(TrainingSample<T> t)` Add a single example to the current training set and train the classifier

Method parameters in fr.lip6.classifier with type arguments of type TrainingSample
`void` | `SMOSVM.setTrain(java.util.ArrayList<TrainingSample<T>> t)`
`void` | `DoublePegasosSVM.train(java.util.ArrayList<TrainingSample<double[]>> l)`
`void` | `SMOSVM.train(java.util.ArrayList<TrainingSample<T>> t)`
`void` | `EnhancedSMOSVM.train(java.util.ArrayList<TrainingSample<T>> t)`
`void` | `SimpleMKL.train(java.util.ArrayList<TrainingSample<T>> list)` optimisation des poids d'après l'algorithme SimpleMKL d'Alain Rakotomamonjy
`void` | `PegasosSVM.train(java.util.ArrayList<TrainingSample<T>> l)`
`void` | `ParzenClassifier.train(java.util.ArrayList<TrainingSample<T>> t)`
`void` | `Classifier.train(java.util.ArrayList<TrainingSample<T>> l)` Replace the current training and train the classifier

Uses of TrainingSample in fr.lip6.kernel

Method parameters in fr.lip6.kernel with type arguments of type TrainingSample
`double[][]` | `CMKernel.getKernelMatrix(java.util.ArrayList<TrainingSample<T>> e)`
`double[][]` | `ThreadedKernel.getKernelMatrix(java.util.ArrayList<TrainingSample<T>> e)`
`double[][]` | `Kernel.getKernelMatrix(java.util.ArrayList<TrainingSample<T>> e)` return the Gram Matrix of this kernel computed on given samples
`double[][]` | `Kernel.getNormalizedKernelMatrix(java.util.ArrayList<TrainingSample<T>> e)` return the Gram Matrix of this kernel computed on given samples

Uses of TrainingSample in fr.lip6.kernel.adaptative

Method parameters in fr.lip6.kernel.adaptative with type arguments of type TrainingSample
`double[][]` | `WeightedSumKernel.getKernelMatrix(java.util.ArrayList<TrainingSample<T>> e)`
`double[][]` | `ThreadedSumKernel.getKernelMatrix(java.util.ArrayList<TrainingSample<T>> e)`

Overview | Package | Class | Use | Tree | Deprecated | Index | Help
PREV NEXT | FRAMES NO FRAMES