Specifies the parameters for the MeanErrorLossLayerParameter. More...

Inheritance diagram for MyCaffe.param.MeanErrorLossParameter:

Public Member Functions
	MeanErrorLossParameter ()
	Constructor for the parameter. More...

override object	Load (System.IO.BinaryReader br, bool bNewInstance=true)
	Load the parameter from a binary reader. More...

override void	Copy (LayerParameterBase src)
	Copy on parameter to another. More...

override LayerParameterBase	Clone ()
	Creates a new copy of this instance of the parameter. More...

override RawProto	ToProto (string strName)
	Convert the parameter into a RawProto. More...

Public Member Functions inherited from MyCaffe.param.LayerParameterBase
	LayerParameterBase ()
	Constructor for the parameter. More...

virtual string	PrepareRunModelInputs ()
	This method gives derivative classes a chance specify model inputs required by the run model. More...

virtual void	PrepareRunModel (LayerParameter p)
	This method gives derivative classes a chance to prepare the layer for a run-model. More...

void	Save (BinaryWriter bw)
	Save this parameter to a binary writer. More...

abstract object	Load (BinaryReader br, bool bNewInstance=true)
	Load the parameter from a binary reader. More...

Public Member Functions inherited from MyCaffe.basecode.BaseParameter
	BaseParameter ()
	Constructor for the parameter. More...

virtual bool	Compare (BaseParameter p)
	Compare this parameter to another parameter. More...

Static Public Member Functions
static MeanErrorLossParameter	FromProto (RawProto rp)
	Parses the parameter from a RawProto. More...

Static Public Member Functions inherited from MyCaffe.basecode.BaseParameter
static double	ParseDouble (string strVal)
	Parse double values using the US culture if the decimal separator = '.', then using the native culture, and if then lastly trying the US culture to handle prototypes containing '.' as the separator, yet parsed in a culture that does not use '.' as a decimal. More...

static bool	TryParse (string strVal, out double df)
	Parse double values using the US culture if the decimal separator = '.', then using the native culture, and if then lastly trying the US culture to handle prototypes containing '.' as the separator, yet parsed in a culture that does not use '.' as a decimal. More...

static float	ParseFloat (string strVal)
	Parse float values using the US culture if the decimal separator = '.', then using the native culture, and if then lastly trying the US culture to handle prototypes containing '.' as the separator, yet parsed in a culture that does not use '.' as a decimal. More...

static bool	TryParse (string strVal, out float f)
	Parse doufloatble values using the US culture if the decimal separator = '.', then using the native culture, and if then lastly trying the US culture to handle prototypes containing '.' as the separator, yet parsed in a culture that does not use '.' as a decimal. More...

Properties
int	axis `[getset]`
	[optional, default = 1] Specifies the axis of the probability. More...

MEAN_ERROR	mean_error_type `[getset]`
	[optional, default = MSE] Specifies the type of mean error to use. More...

Additional Inherited Members
Public Types inherited from MyCaffe.param.LayerParameterBase
enum	LABEL_TYPE { NONE , SINGLE , MULTIPLE , ONLY_ONE }
	Defines the label type. More...

Detailed Description

Specifies the parameters for the MeanErrorLossLayerParameter.

Used with regression models, such as those used with time-series prediction.

See also: Methods for forecasts of continuous variables by WCRP, 2017.; MAD vs RMSE vs MAE vs MSLE vs R^2: When to use which?, StackExchange, 2018.; Mean Absolute Error by Peltarion.

Definition at line 22 of file MeanErrorLossParameter.cs.

Constructor & Destructor Documentation

◆ MeanErrorLossParameter()

MyCaffe.param.MeanErrorLossParameter.MeanErrorLossParameter ( )

Constructor for the parameter.

Definition at line 29 of file MeanErrorLossParameter.cs.

Member Function Documentation

◆ Clone()

override LayerParameterBase MyCaffe.param.MeanErrorLossParameter.Clone ( )

virtual

Creates a new copy of this instance of the parameter.

Returns: A new instance of this parameter is returned.

Implements MyCaffe.param.LayerParameterBase.

Definition at line 73 of file MeanErrorLossParameter.cs.

◆ Copy()

override void MyCaffe.param.MeanErrorLossParameter.Copy ( LayerParameterBase src )

virtual

Copy on parameter to another.

Parameters

src	Specifies the parameter to copy.

Implements MyCaffe.param.LayerParameterBase.

Definition at line 65 of file MeanErrorLossParameter.cs.

◆ FromProto()

static MeanErrorLossParameter MyCaffe.param.MeanErrorLossParameter.FromProto ( RawProto rp )

static

Parses the parameter from a RawProto.

Parameters

rp	Specifies the RawProto to parse.

Returns: A new instance of the parameter is returned.

Definition at line 100 of file MeanErrorLossParameter.cs.

◆ Load()

override object MyCaffe.param.MeanErrorLossParameter.Load	(	System.IO.BinaryReader	br,
		bool	bNewInstance = `true`
	)

Load the parameter from a binary reader.

Parameters

br	Specifies the binary reader.
bNewInstance	When true a new instance is created (the default), otherwise the existing instance is loaded from the binary reader.

Returns: Returns an instance of the parameter.

Definition at line 53 of file MeanErrorLossParameter.cs.

◆ ToProto()

override RawProto MyCaffe.param.MeanErrorLossParameter.ToProto ( string strName )

virtual

Convert the parameter into a RawProto.

Parameters

strName Specifies the name to associate with the RawProto.

Returns: The new RawProto is returned.

Implements MyCaffe.basecode.BaseParameter.

Definition at line 85 of file MeanErrorLossParameter.cs.

Property Documentation

◆ axis

int MyCaffe.param.MeanErrorLossParameter.axis

getset

[optional, default = 1] Specifies the axis of the probability.

Definition at line 37 of file MeanErrorLossParameter.cs.

◆ mean_error_type

MEAN_ERROR MyCaffe.param.MeanErrorLossParameter.mean_error_type

getset

[optional, default = MSE] Specifies the type of mean error to use.

Definition at line 46 of file MeanErrorLossParameter.cs.

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

C:/Data/Data/SS_Projects/Intelligence/GitHub/MyCaffe/MyCaffe/param.beta/MeanErrorLossParameter.cs

Public Member Functions

Static Public Member Functions

Properties

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ MeanErrorLossParameter()

Member Function Documentation

◆ Clone()

◆ Copy()

◆ FromProto()

◆ Load()

◆ ToProto()

Property Documentation

◆ axis

◆ mean_error_type