IG::Neural::NeuralTrainingParameters::ComparerBase Class Reference

Base comparer class (implementation of the IComparer<NeuralTrainingParameters> interface) for conmparing objects of type NeuralTrainingParameters More...

Collaboration diagram for IG::Neural::NeuralTrainingParameters::ComparerBase:

List of all members.

Protected Member Functions
double	OutputNorm (IVector vec)
Protected Attributes
IVector	_outputScalingLengths
bool	_compareMinError = false
int	_numLastErrors = 1
int	_numBundles = 0
bool	_compareByTrainingRmsError = true
bool	_compareByTrainingMaxError = false
bool	_compareByVerificationRmsError = false
bool	_compareByVerificationMaxError = false
Properties
IVector	OutputScalingLengths [get, set]
	Vector of scaling lengths for calculation of weighted norms.
bool	CompareMinError [get, set]
	Whether the min error in convergence table is used for comparison when errors are compared. If false then mean value of last errors is used.
int	NumLastErrors [get, set]
	Number of last errors in convergence list for calculataing the mean value of error. The default valeu is 1 which represent the last error in the converhence list.
int	NumBundles [get, set]
	Number of bundles where sorting of convergences stars. The default valeu is 0 which represent normal sorting after the training is done.
bool	CompareByTrainingRmsError [get, set]
	Whether training RMS errors from convergence tavble are compared.
bool	CompareByTrainingMaxError [get, set]
	Whether Maximal absolute training errors from convergence tavble are compared.
bool	CompareByVerificationRmsError [get, set]
	Whether verification RMS errors from convergence tavble are compared.
bool	CompareByVerificationMaxError [get, set]
	Whether Maximal absolute verification errors from convergence tavble are compared.
Private Member Functions
int IComparer < NeuralTrainingParameters >.	Compare (NeuralTrainingParameters a, NeuralTrainingParameters b)

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Detailed Description

Base comparer class (implementation of the IComparer<NeuralTrainingParameters> interface) for conmparing objects of type NeuralTrainingParameters

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Member Function Documentation

double IG::Neural::NeuralTrainingParameters::ComparerBase::OutputNorm

(

IVector

vec

)

[inline, protected]

int IComparer<NeuralTrainingParameters>. IG::Neural::NeuralTrainingParameters::ComparerBase::Compare	(	NeuralTrainingParameters	a,
		NeuralTrainingParameters	b
	)		[inline, private]

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Member Data Documentation

IVector IG::Neural::NeuralTrainingParameters::ComparerBase::_outputScalingLengths [protected]

bool IG::Neural::NeuralTrainingParameters::ComparerBase::_compareMinError = false [protected]

int IG::Neural::NeuralTrainingParameters::ComparerBase::_numLastErrors = 1 [protected]

int IG::Neural::NeuralTrainingParameters::ComparerBase::_numBundles = 0 [protected]

bool IG::Neural::NeuralTrainingParameters::ComparerBase::_compareByTrainingRmsError = true [protected]

bool IG::Neural::NeuralTrainingParameters::ComparerBase::_compareByTrainingMaxError = false [protected]

bool IG::Neural::NeuralTrainingParameters::ComparerBase::_compareByVerificationRmsError = false [protected]

bool IG::Neural::NeuralTrainingParameters::ComparerBase::_compareByVerificationMaxError = false [protected]

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Property Documentation

IVector IG::Neural::NeuralTrainingParameters::ComparerBase::OutputScalingLengths [get, set]

Vector of scaling lengths for calculation of weighted norms.

bool IG::Neural::NeuralTrainingParameters::ComparerBase::CompareMinError [get, set]

Whether the min error in convergence table is used for comparison when errors are compared. If false then mean value of last errors is used.

int IG::Neural::NeuralTrainingParameters::ComparerBase::NumLastErrors [get, set]

Number of last errors in convergence list for calculataing the mean value of error. The default valeu is 1 which represent the last error in the converhence list.

int IG::Neural::NeuralTrainingParameters::ComparerBase::NumBundles [get, set]

Number of bundles where sorting of convergences stars. The default valeu is 0 which represent normal sorting after the training is done.

bool IG::Neural::NeuralTrainingParameters::ComparerBase::CompareByTrainingRmsError [get, set]

Whether training RMS errors from convergence tavble are compared.

bool IG::Neural::NeuralTrainingParameters::ComparerBase::CompareByTrainingMaxError [get, set]

Whether Maximal absolute training errors from convergence tavble are compared.

bool IG::Neural::NeuralTrainingParameters::ComparerBase::CompareByVerificationRmsError [get, set]

Whether verification RMS errors from convergence tavble are compared.

bool IG::Neural::NeuralTrainingParameters::ComparerBase::CompareByVerificationMaxError [get, set]

Whether Maximal absolute verification errors from convergence tavble are compared.

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The documentation for this class was generated from the following file:

• NeuralTrainingParameters.cs