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## T

takeStep(int, int, double) - Method in class fr.lip6.classifier.EnhancedSMOSVM
  Method solving for the Lagrange multipliers for two instances.
TestSimpleSVM - Class in fr.lip6.test
TestSimpleSVM() - Constructor for class fr.lip6.test.TestSimpleSVM
ThreadedKernel<T> - Class in fr.lip6.kernel
  Simple multithreaded implementation over a given Kernel.
ThreadedKernel(Kernel<T>) - Constructor for class fr.lip6.kernel.ThreadedKernel
  MultiThread the given kernel
ThreadedSumKernel<T> - Class in fr.lip6.kernel.adaptative
  Major kernel computed as a weighted sum of minor kernels : K = w_i * k_i
  Computation of the kernel matrix is done by running a thread on sub matrices.
ThreadedSumKernel() - Constructor for class fr.lip6.kernel.adaptative.ThreadedSumKernel
ThreadedSumKernel(Hashtable<Kernel<T>, Double>) - Constructor for class fr.lip6.kernel.adaptative.ThreadedSumKernel
  Sets the weights to h.
toString() - Method in class fr.lip6.kernel.Kernel
train(TrainingSample<T>) - Method in interface fr.lip6.classifier.Classifier
  Add a single example to the current training set and train the classifier
train(ArrayList<TrainingSample<T>>) - Method in interface fr.lip6.classifier.Classifier
  Replace the current training and train the classifier
train(ArrayList<TrainingSample<double[]>>) - Method in class fr.lip6.classifier.DoublePegasosSVM
train(TrainingSample<double[]>) - Method in class fr.lip6.classifier.DoublePegasosSVM
train(TrainingSample<T>) - Method in class fr.lip6.classifier.EnhancedSMOSVM
train(ArrayList<TrainingSample<T>>) - Method in class fr.lip6.classifier.EnhancedSMOSVM
train(TrainingSample<T>) - Method in class fr.lip6.classifier.ParzenClassifier
train(ArrayList<TrainingSample<T>>) - Method in class fr.lip6.classifier.ParzenClassifier
train(ArrayList<TrainingSample<T>>) - Method in class fr.lip6.classifier.PegasosSVM
train(TrainingSample<T>) - Method in class fr.lip6.classifier.PegasosSVM
train(TrainingSample<T>) - Method in class fr.lip6.classifier.SimpleMKL
train(ArrayList<TrainingSample<T>>) - Method in class fr.lip6.classifier.SimpleMKL
  optimisation des poids d'après l'algorithme SimpleMKL d'Alain Rakotomamonjy
train(TrainingSample<T>) - Method in class fr.lip6.classifier.SMOSVM
train(ArrayList<TrainingSample<T>>) - Method in class fr.lip6.classifier.SMOSVM
train(T) - Method in interface fr.lip6.density.DensityFunction
  ajoute un exemple à l'ensemble d'apprentissage et ré-entraîne l'estimateur.
train(ArrayList<T>) - Method in interface fr.lip6.density.DensityFunction
  Entraîne l'estimateur de densité sur l'ensemble d'apprentissage fourni en argument.
train(T) - Method in class fr.lip6.density.ParzenDensity
train(ArrayList<T>) - Method in class fr.lip6.density.ParzenDensity
train(T) - Method in class fr.lip6.density.SMODensity
train(ArrayList<T>) - Method in class fr.lip6.density.SMODensity
TrainingSample<T> - Class in fr.lip6.type
  Simple class of training sample that contains the generic of sample and the associated label.
TrainingSample(T, int) - Constructor for class fr.lip6.type.TrainingSample

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