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GradientDescent Properties

The GradientDescent type exposes the following members.

Public propertyFunction
Gets or sets the function to be optimized.
(Inherited from BaseOptimizationMethod.)
Public propertyGradient
Gets or sets a function returning the gradient vector of the function to be optimized for a given value of its free parameters.
(Inherited from BaseGradientOptimizationMethod.)
Public propertyIterations
Gets or sets the maximum number of iterations performed by the learning algorithm. Default is 0.
Public propertyLearningRate
Gets or sets the learning rate. Default is 1e-3.
Public propertyNumberOfVariables
Gets the number of variables (free parameters) in the optimization problem.
(Inherited from BaseOptimizationMethod.)
Public propertySolution
Gets the current solution found, the values of the parameters which optimizes the function.
(Inherited from BaseOptimizationMethod.)
Public propertyToken
Gets or sets a cancellation token that can be used to stop the learning algorithm while it is running.
(Inherited from BaseOptimizationMethod.)
Public propertyTolerance
Gets or sets the maximum change in the average log-likelihood after an iteration of the algorithm used to detect convergence. Default is 1e-5.
Public propertyValue
Gets the output of the function at the current Solution.
(Inherited from BaseOptimizationMethod.)
See Also