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BaseLeastSquaresMethod Class |
Base class for least-squares optimizers implementing the ILeastSquaresMethod interface.
Inheritance HierarchySystemObject
Accord.MachineLearningParallelLearningBase
Accord.Math.OptimizationBaseLeastSquaresMethod
Accord.Math.OptimizationGaussNewton
Accord.Math.OptimizationLevenbergMarquardt
Accord.MachineLearningParallelLearningBase
Accord.Math.OptimizationBaseLeastSquaresMethod
Accord.Math.OptimizationGaussNewton
Accord.Math.OptimizationLevenbergMarquardt
Namespace: Accord.Math.Optimization
Assembly: Accord.Math (in Accord.Math.dll) Version: 3.8.0
SyntaxThe BaseLeastSquaresMethod type exposes the following members.
Constructors| Name | Description | |
|---|---|---|
 | BaseLeastSquaresMethod |
Initializes a new instance of the BaseLeastSquaresMethod class.
|
Properties| Name | Description | |
|---|---|---|
 | Convergence |
Gets or sets the convergence verification method.
|
 | CurrentIteration |
Gets the current iteration number.
|
| Function |
Gets or sets a parameterized model function mapping input vectors
into output values, whose optimum parameters must be found.
|
| Gradient |
Gets or sets a function that computes the gradient vector in respect
to the function parameters, given a set of input and output values.
|
| HasConverged |
Gets whether the algorithm has converged.
|
| Iterations | Obsolete.
Please use MaxIterations instead.
|
| MaxIterations |
Gets or sets the maximum number of iterations
performed by the iterative algorithm. Default
is 100.
|
| NumberOfParameters |
Gets the number of variables (free parameters) in the optimization problem.
|
| NumberOfVariables | Obsolete.
Gets the number of variables (free parameters) in the optimization problem.
|
| ParallelOptions |
Gets or sets the parallelization options for this algorithm.
(Inherited from ParallelLearningBase.) |
| Solution |
Gets the solution found, the values of the parameters which
optimizes the function, in a least squares sense.
|
| Token |
Gets or sets a cancellation token that can be used
to cancel the algorithm while it is running.
(Inherited from ParallelLearningBase.) |
| Tolerance |
Gets or sets the maximum relative change in the watched value
after an iteration of the algorithm used to detect convergence.
Default is zero.
|
| Value |
Gets the value at the solution found. This should be
the minimum value found for the objective function.
|
Methods| Name | Description | |
|---|---|---|
| ComputeError |
Compute model error for a given data set.
|
| Equals | Determines whether the specified object is equal to the current object. (Inherited from Object.) |
 | Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.) |
| GetHashCode | Serves as the default hash function. (Inherited from Object.) |
| GetType | Gets the Type of the current instance. (Inherited from Object.) |
| Initialize |
This method should be implemented by child classes to initialize
their fields once the NumberOfParameters is known.
|
| MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object.) |
| ToString | Returns a string that represents the current object. (Inherited from Object.) |
Extension Methods| Name | Description | |
|---|---|---|
 | HasMethod |
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.) |
| IsEqual |
Compares two objects for equality, performing an elementwise
comparison if the elements are vectors or matrices.
(Defined by Matrix.) |
| To(Type) | Overloaded.
Converts an object into another type, irrespective of whether
the conversion can be done at compile time or not. This can be
used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.) |
| ToT | Overloaded.
Converts an object into another type, irrespective of whether
the conversion can be done at compile time or not. This can be
used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.) |
See Also