Contains algorithms for training Support Vector Machines (SVMs).
Class Description AveragedStochasticGradientDescentAveraged Stochastic Gradient Descent (ASGD) for training linear support vector machines.
AveragedStochasticGradientDescentTKernelAveraged Stochastic Gradient Descent (ASGD) for training linear support vector machines.
AveragedStochasticGradientDescentTKernel, TInputAveraged Stochastic Gradient Descent (ASGD) for training linear support vector machines.
AveragedStochasticGradientDescentTKernel, TInput, TLossAveraged Stochastic Gradient Descent (ASGD) for training linear support vector machines.
BaseAveragedStochasticGradientDescentTModel, TKernel, TInput, TLossBase class for Averaged Stochastic Gradient Descent algorithm implementations.
BaseFanChenLinSupportVectorRegressionTModel, TKernel, TInputBase class for Fan-Chen-Lin (LibSVM) regression algorithms.
BaseLinearCoordinateDescentTModel, TKernelBase class for linear coordinate descent learning algorithm.
BaseLinearDualCoordinateDescentTModel, TKernel, TInputBase class for Linear Dual Coordinate Descent.
BaseLinearNewtonMethodTModel, TKernelBase class for L2-regularized L2-loss linear support vector classification (primal).
BaseLinearNewtonMethodTModel, TKernel, TInputL2-regularized L2-loss linear support vector classification (primal).
BaseLinearRegressionCoordinateDescentTModel, TKernel, TInputBase class for Coordinate descent algorithm for the L1 or L2-loss linear Support Vector Regression (epsilon-SVR) learning problem in the dual form (-s 12 and -s 13).
BaseLinearRegressionNewtonMethodTModel, TKernel, TInputBase class for newton method for linear regression learning algorithm.
BaseMulticlassSupportVectorLearningTBinary, TKernel, TModelBase class for multi-class support vector learning algorithms.
BaseMulticlassSupportVectorLearningTInput, TBinary, TKernel, TModelBase class for multi-class support vector learning algorithms.
BaseMultilabelSupportVectorLearningTInput, TBinary, TKernel, TModelBase class for multi-label support vector learning algorithms.
BaseOneclassSupportVectorLearningTModel, TKernel, TInputOne-class Support Vector Machine Learning Algorithm.
BaseProbabilisticCoordinateDescentTModel, TKernel, TInputBase class for L1-regularized logistic regression (probabilistic SVM) learning algorithm (-s 6).
BaseProbabilisticDualCoordinateDescentTModel, TKernel, TInputBase class for L2-regularized logistic regression (probabilistic support vector machine) learning algorithm in the dual form (-s 7).
BaseProbabilisticNewtonMethodTModel, TKernel, TInputBase class for probabilistic Newton Method learning.
BaseSequentialMinimalOptimizationTModel, TKernel, TInputBase class for Sequential Minimal Optimization.
BaseSequentialMinimalOptimizationRegressionTModel, TKernel, TInputBase class for Sequential Minimal Optimization for regression.
BaseStochasticGradientDescentTModel, TKernel, TInput, TLossBase class for Averaged Stochastic Gradient Descent algorithm implementations.
BaseSupportVectorCalibrationTModel, TKernel, TInputBase class for
SupportVectorMachinecalibration algorithms.
BaseSupportVectorClassificationTModel, TKernel, TInputBase class for
SupportVectorMachinelearning algorithms.
BaseSupportVectorRegressionTModel, TKernel, TInputBase class for
SupportVectorMachineregression learning algorithms.
FanChenLinSupportVectorRegressionSupport vector regression using
FanChenLinQuadraticOptimization(LibSVM) algorithm.
FanChenLinSupportVectorRegressionTKernelSupport vector regression using
FanChenLinQuadraticOptimization(LibSVM) algorithm.
FanChenLinSupportVectorRegressionTKernel, TInputSupport vector regression using
FanChenLinQuadraticOptimization(LibSVM) algorithm.
LeastSquaresLearningLeast Squares SVM (LS-SVM) learning algorithm.
LeastSquaresLearningTKernel, TInputLeast Squares SVM (LS-SVM) learning algorithm.
LeastSquaresLearningBaseTModel, TKernel, TInputBase class for Least Squares SVM (LS-SVM) learning algorithm.
LinearCoordinateDescentL1-regularized L2-loss support vector Support Vector Machine learning (-s 5).
LinearCoordinateDescentTKernelL1-regularized L2-loss support vector Support Vector Machine learning (-s 5).
LinearDualCoordinateDescentL2-regularized, L1 or L2-loss dual formulation Support Vector Machine learning (-s 1 and -s 3).
LinearDualCoordinateDescentTKernelL2-regularized, L1 or L2-loss dual formulation Support Vector Machine learning (-s 1 and -s 3).
LinearDualCoordinateDescentTKernel, TInputL2-regularized, L1 or L2-loss dual formulation Support Vector Machine learning (-s 1 and -s 3).
LinearNewtonMethodL2-regularized L2-loss linear support vector classification (primal).
LinearNewtonMethodTKernel, TInputL2-regularized L2-loss linear support vector classification (primal).
LinearRegressionCoordinateDescentCoordinate descent algorithm for the L1 or L2-loss linear Support Vector Regression (epsilon-SVR) learning problem in the dual form (-s 12 and -s 13).
LinearRegressionCoordinateDescentTKernel, TInputCoordinate descent algorithm for the L1 or L2-loss linear Support Vector Regression (epsilon-SVR) learning problem in the dual form (-s 12 and -s 13).
LinearRegressionNewtonMethodL2-regularized L2-loss linear support vector regression (SVR) learning algorithm in the primal formulation (-s 11).
LinearRegressionNewtonMethodTKernel, TInputL2-regularized L2-loss linear support vector regression (SVR) learning algorithm in the primal formulation (-s 11).
MulticlassSupportVectorLearning Obsolete.One-against-one Multi-class Support Vector Machine Learning Algorithm
MulticlassSupportVectorLearningTKernelOne-against-one Multi-class Support Vector Machine Learning Algorithm
MulticlassSupportVectorLearningTKernel, TInputOne-against-one Multi-class Support Vector Machine Learning Algorithm
MultilabelSupportVectorLearning Obsolete.Obsolete.
MultilabelSupportVectorLearningTKernelOne-against-all Multi-label Support Vector Machine Learning Algorithm
MultilabelSupportVectorLearningTKernel, TInputOne-against-all Multi-label Support Vector Machine Learning Algorithm
OneclassSupportVectorLearning Obsolete.One-class Support Vector Machine learning algorithm.
OneclassSupportVectorLearningTKernelOne-class Support Vector Machine learning algorithm.
OneclassSupportVectorLearningTKernel, TInputOne-class Support Vector Machine learning algorithm.
ProbabilisticCoordinateDescentL1-regularized logistic regression (probabilistic SVM) learning algorithm (-s 6).
ProbabilisticCoordinateDescentTKernel, TInputL1-regularized logistic regression (probabilistic SVM) learning algorithm (-s 6).
ProbabilisticDualCoordinateDescentL2-regularized logistic regression (probabilistic support vector machine) learning algorithm in the dual form (-s 7).
ProbabilisticDualCoordinateDescentTKernel, TInputL2-regularized logistic regression (probabilistic support vector machine) learning algorithm in the dual form (-s 7).
ProbabilisticNewtonMethodL2-regularized L2-loss logistic regression (probabilistic support vector machine) learning algorithm in the primal.
ProbabilisticNewtonMethodTKernelL2-regularized L2-loss logistic regression (probabilistic support vector machine) learning algorithm in the primal.
ProbabilisticNewtonMethodTKernel, TInputL2-regularized L2-loss logistic regression (probabilistic support vector machine) learning algorithm in the primal.
ProbabilisticOutputCalibrationProbabilistic Output Calibration for Linear machines.
ProbabilisticOutputCalibrationTKernelProbabilistic Output Calibration for Kernel machines.
ProbabilisticOutputCalibrationTKernel, TInputProbabilistic Output Calibration for structured Kernel machines.
ProbabilisticOutputCalibrationBaseTModel, TKernel, TInputProbabilistic Output Calibration.
SequentialMinimalOptimizationSequential Minimal Optimization (SMO) Algorithm
SequentialMinimalOptimizationTKernelSequential Minimal Optimization (SMO) Algorithm.
SequentialMinimalOptimizationTKernel, TInputSequential Minimal Optimization (SMO) Algorithm (for arbitrary data types).
SequentialMinimalOptimizationRegressionSequential Minimal Optimization (SMO) Algorithm for Regression. Warning: this code is contained in a GPL assembly. Thus, if you link against this assembly, you should comply with the GPL license.
SequentialMinimalOptimizationRegressionTKernelSequential Minimal Optimization (SMO) Algorithm for Regression. Warning: this code is contained in a GPL assembly. Thus, if you link against this assembly, you should comply with the GPL license.
SequentialMinimalOptimizationRegressionTKernel, TInputSequential Minimal Optimization (SMO) Algorithm for Regression. Warning: this code is contained in a GPL assembly. Thus, if you link against this assembly, you should comply with the GPL license.
StochasticGradientDescentStochastic Gradient Descent (SGD) for training linear support vector machines.
StochasticGradientDescentTKernelStochastic Gradient Descent (SGD) for training linear support vector machines.
StochasticGradientDescentTKernel, TInputStochastic Gradient Descent (SGD) for training linear support vector machines.
StochasticGradientDescentTKernel, TInput, TLossStochastic Gradient Descent (SGD) for training linear support vector machines.
SupportVectorReductionExact support vector reduction through linear dependency elimination.
SupportVectorReductionTKernelExact support vector reduction through linear dependency elimination.
SupportVectorReductionTKernel, TInputExact support vector reduction through linear dependency elimination.
SupportVectorReductionBaseTModel, TKernel, TInputExact support vector reduction through linear dependency elimination.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4