Definition at line 48 of file TNeuron.h.

Public Types
enum	ENeuronType { kOff, kLinear, kSigmoid, kTanh, kGauss, kSoftmax, kExternal }

Public Types inherited from TObject
enum	EStatusBits { kCanDelete = BIT(0), kMustCleanup = BIT(3), kObjInCanvas = BIT(3), kIsReferenced = BIT(4), kHasUUID = BIT(5), kCannotPick = BIT(6), kNoContextMenu = BIT(8), kInvalidObject = BIT(13) }

enum	{ kIsOnHeap = 0x01000000, kNotDeleted = 0x02000000, kZombie = 0x04000000, kBitMask = 0x00ffffff }

enum	{ kSingleKey = BIT(0), kOverwrite = BIT(1), kWriteDelete = BIT(2) }

Public Member Functions
	TNeuron (ENeuronType type=kSigmoid, const char name="", const char title="", const char extF="", const char extD="")

virtual	~TNeuron ()

TSynapse *	GetPre (Int_t n) const

TSynapse *	GetPost (Int_t n) const

TNeuron *	GetInLayer (Int_t n) const

TTreeFormula *	UseBranch (TTree , const char )
	Sets a formula that can be used to make the neuron an input. More...

Double_t	GetInput () const
	Returns neuron input. More...

Double_t	GetValue () const
	Computes the output using the appropriate function and all the weighted inputs, or uses the branch as input. More...

Double_t	GetDerivative () const
	computes the derivative for the appropriate function at the working point More...

Double_t	GetError () const
	Computes the error for output neurons. More...

Double_t	GetTarget () const
	Computes the normalized target pattern for output neurons. More...

Double_t	GetDeDw () const
	Computes the derivative of the error wrt the neuron weight. More...

Double_t	GetBranch () const
	Returns the formula value. More...

ENeuronType	GetType () const
	Returns the neuron type. More...

void	SetWeight (Double_t w)
	Sets the neuron weight to w. More...

Double_t	GetWeight () const

void	SetNormalisation (Double_t mean, Double_t RMS)
	Sets the normalization variables. More...

const Double_t *	GetNormalisation () const

void	SetNewEvent () const
	Inform the neuron that inputs of the network have changed, so that the buffered values have to be recomputed. More...

void	SetDEDw (Double_t in)
	Sets the derivative of the total error wrt the neuron weight. More...

Double_t	GetDEDw () const

void	ForceExternalValue (Double_t value)
	Uses the branch type to force an external value. More...

void	AddInLayer (TNeuron *)
	Tells a neuron which neurons form its layer (including itself). More...

Public Member Functions inherited from TNamed
	TNamed ()

	TNamed (const char name, const char title)

	TNamed (const TString &name, const TString &title)

	TNamed (const TNamed &named)

TNamed &	operator= (const TNamed &rhs)
	TNamed assignment operator. More...

virtual	~TNamed ()

virtual void	Clear (Option_t *option="")
	Set name and title to empty strings (""). More...

virtual TObject *	Clone (const char *newname="") const
	Make a clone of an object using the Streamer facility. More...

virtual Int_t	Compare (const TObject *obj) const
	Compare two TNamed objects. More...

virtual void	Copy (TObject &named) const
	Copy this to obj. More...

virtual void	FillBuffer (char *&buffer)
	Encode TNamed into output buffer. More...

virtual const char *	GetName () const
	Returns name of object. More...

virtual const char *	GetTitle () const
	Returns title of object. More...

virtual ULong_t	Hash () const
	Return hash value for this object. More...

virtual Bool_t	IsSortable () const

virtual void	SetName (const char *name)
	Change (i.e. More...

virtual void	SetNameTitle (const char name, const char title)
	Change (i.e. set) all the TNamed parameters (name and title). More...

virtual void	SetTitle (const char *title="")
	Change (i.e. set) the title of the TNamed. More...

virtual void	ls (Option_t *option="") const
	List TNamed name and title. More...

virtual void	Print (Option_t *option="") const
	Print TNamed name and title. More...

virtual Int_t	Sizeof () const
	Return size of the TNamed part of the TObject. More...

Public Member Functions inherited from TObject
	TObject ()

	TObject (const TObject &object)
	TObject copy ctor. More...

TObject &	operator= (const TObject &rhs)
	TObject assignment operator. More...

virtual	~TObject ()
	TObject destructor. More...

virtual void	AppendPad (Option_t *option="")
	Append graphics object to current pad. More...

virtual void	Browse (TBrowser *b)
	Browse object. May be overridden for another default action. More...

virtual const char *	ClassName () const
	Returns name of class to which the object belongs. More...

virtual void	Delete (Option_t *option="")
	Delete this object. More...

virtual Int_t	DistancetoPrimitive (Int_t px, Int_t py)
	Computes distance from point (px,py) to the object. More...

virtual void	Draw (Option_t *option="")
	Default Draw method for all objects. More...

virtual void	DrawClass () const
	Draw class inheritance tree of the class to which this object belongs. More...

virtual TObject *	DrawClone (Option_t *option="") const
	Draw a clone of this object in the current pad. More...

virtual void	Dump () const
	Dump contents of object on stdout. More...

virtual void	Execute (const char method, const char params, Int_t *error=0)
	Execute method on this object with the given parameter string, e.g. More...

virtual void	Execute (TMethod method, TObjArray params, Int_t *error=0)
	Execute method on this object with parameters stored in the TObjArray. More...

virtual void	ExecuteEvent (Int_t event, Int_t px, Int_t py)
	Execute action corresponding to an event at (px,py). More...

virtual TObject *	FindObject (const char *name) const
	Must be redefined in derived classes. More...

virtual TObject *	FindObject (const TObject *obj) const
	Must be redefined in derived classes. More...

virtual Option_t *	GetDrawOption () const
	Get option used by the graphics system to draw this object. More...

virtual UInt_t	GetUniqueID () const
	Return the unique object id. More...

virtual const char *	GetIconName () const
	Returns mime type name of object. More...

virtual Option_t *	GetOption () const

virtual char *	GetObjectInfo (Int_t px, Int_t py) const
	Returns string containing info about the object at position (px,py). More...

virtual Bool_t	HandleTimer (TTimer *timer)
	Execute action in response of a timer timing out. More...

virtual Bool_t	InheritsFrom (const char *classname) const
	Returns kTRUE if object inherits from class "classname". More...

virtual Bool_t	InheritsFrom (const TClass *cl) const
	Returns kTRUE if object inherits from TClass cl. More...

virtual void	Inspect () const
	Dump contents of this object in a graphics canvas. More...

virtual Bool_t	IsFolder () const
	Returns kTRUE in case object contains browsable objects (like containers or lists of other objects). More...

virtual Bool_t	IsEqual (const TObject *obj) const
	Default equal comparison (objects are equal if they have the same address in memory). More...

Bool_t	IsOnHeap () const

Bool_t	IsZombie () const

virtual Bool_t	Notify ()
	This method must be overridden to handle object notification. More...

virtual void	Paint (Option_t *option="")
	This method must be overridden if a class wants to paint itself. More...

virtual void	Pop ()
	Pop on object drawn in a pad to the top of the display list. More...

virtual Int_t	Read (const char *name)
	Read contents of object with specified name from the current directory. More...

virtual void	RecursiveRemove (TObject *obj)
	Recursively remove this object from a list. More...

virtual void	SaveAs (const char filename="", Option_t option="") const
	Save this object in the file specified by filename. More...

virtual void	SavePrimitive (std::ostream &out, Option_t *option="")
	Save a primitive as a C++ statement(s) on output stream "out". More...

virtual void	SetDrawOption (Option_t *option="")
	Set drawing option for object. More...

virtual void	SetUniqueID (UInt_t uid)
	Set the unique object id. More...

virtual void	UseCurrentStyle ()
	Set current style settings in this object This function is called when either TCanvas::UseCurrentStyle or TROOT::ForceStyle have been invoked. More...

virtual Int_t	Write (const char *name=0, Int_t option=0, Int_t bufsize=0)
	Write this object to the current directory. More...

virtual Int_t	Write (const char *name=0, Int_t option=0, Int_t bufsize=0) const
	Write this object to the current directory. More...

void *	operator new (size_t sz)

void *	operator new[] (size_t sz)

void *	operator new (size_t sz, void *vp)

void *	operator new[] (size_t sz, void *vp)

void	operator delete (void *ptr)
	Operator delete. More...

void	operator delete[] (void *ptr)
	Operator delete []. More...

void	SetBit (UInt_t f, Bool_t set)
	Set or unset the user status bits as specified in f. More...

void	SetBit (UInt_t f)

void	ResetBit (UInt_t f)

Bool_t	TestBit (UInt_t f) const

Int_t	TestBits (UInt_t f) const

void	InvertBit (UInt_t f)

virtual void	Info (const char method, const char msgfmt,...) const
	Issue info message. More...

virtual void	Warning (const char method, const char msgfmt,...) const
	Issue warning message. More...

virtual void	Error (const char method, const char msgfmt,...) const
	Issue error message. More...

virtual void	SysError (const char method, const char msgfmt,...) const
	Issue system error message. More...

virtual void	Fatal (const char method, const char msgfmt,...) const
	Issue fatal error message. More...

void	AbstractMethod (const char *method) const
	Use this method to implement an "abstract" method that you don't want to leave purely abstract. More...

void	MayNotUse (const char *method) const
	Use this method to signal that a method (defined in a base class) may not be called in a derived class (in principle against good design since a child class should not provide less functionality than its parent, however, sometimes it is necessary). More...

void	Obsolete (const char method, const char asOfVers, const char *removedFromVers) const
	Use this method to declare a method obsolete. More...

Protected Member Functions
Double_t	Sigmoid (Double_t x) const
	The Sigmoid. More...

Double_t	DSigmoid (Double_t x) const
	The Derivative of the Sigmoid. More...

void	AddPre (TSynapse *)
	Adds a synapse to the neuron as an input This method is used by the TSynapse while connecting two neurons. More...

void	AddPost (TSynapse *)
	Adds a synapse to the neuron as an output This method is used by the TSynapse while connecting two neurons. More...

Protected Member Functions inherited from TObject
void	MakeZombie ()

virtual void	DoError (int level, const char location, const char fmt, va_list va) const
	Interface to ErrorHandler (protected). More...

Private Member Functions
	TNeuron (const TNeuron &)

TNeuron &	operator= (const TNeuron &)

Private Attributes
TObjArray	fpre

TObjArray	fpost

TObjArray	flayer

Double_t	fWeight

Double_t	fNorm [2]

ENeuronType	fType

TFormula *	fExtF

TFormula *	fExtD

TTreeFormula *	fFormula

Int_t	fIndex
	formula to be used for inputs and outputs More...

Bool_t	fNewInput
	index in the formula More...

Double_t	fInput
	do we need to compute fInput again ? More...

Bool_t	fNewValue
	buffer containing the last neuron input More...

Double_t	fValue
	do we need to compute fValue again ? More...

Bool_t	fNewDeriv
	buffer containing the last neuron output More...

Double_t	fDerivative
	do we need to compute fDerivative again ? More...

Bool_t	fNewDeDw
	buffer containing the last neuron derivative More...

Double_t	fDeDw
	do we need to compute fDeDw again ? More...

Double_t	fDEDw
	buffer containing the last derivative of the error More...

Friends
class	TSynapse

Additional Inherited Members
Static Public Member Functions inherited from TObject
static Long_t	GetDtorOnly ()
	Return destructor only flag. More...

static void	SetDtorOnly (void *obj)
	Set destructor only flag. More...

static Bool_t	GetObjectStat ()
	Get status of object stat flag. More...

static void	SetObjectStat (Bool_t stat)
	Turn on/off tracking of objects in the TObjectTable. More...

Protected Attributes inherited from TNamed
TString	fName

TString	fTitle

#include <TMVA/TNeuron.h>

Inheritance diagram for TNeuron:

[legend]

Member Enumeration Documentation

enum TNeuron::ENeuronType

Enumerator
kOff
kLinear
kSigmoid
kTanh
kGauss
kSoftmax
kExternal

Definition at line 52 of file TNeuron.h.

Constructor & Destructor Documentation

TNeuron::TNeuron	(	ENeuronType	type = `kSigmoid`,
		const char *	name = `""`,
		const char *	title = `""`,
		const char *	extF = `""`,
		const char *	extD = `""`
	)

virtual TNeuron::~TNeuron ( )

inlinevirtual

Definition at line 57 of file TNeuron.h.

TNeuron::TNeuron ( const TNeuron & )

private

Member Function Documentation

void TNeuron::AddInLayer ( TNeuron * nearP )

Tells a neuron which neurons form its layer (including itself).

This is needed for self-normalizing functions, like Softmax.

Definition at line 857 of file TNeuron.cxx.

Referenced by TMultiLayerPerceptron::BuildLastLayer(), and TMultiLayerPerceptron::BuildOneHiddenLayer().

void TNeuron::AddPost ( TSynapse * post )

protected

Adds a synapse to the neuron as an output This method is used by the TSynapse while connecting two neurons.

Definition at line 846 of file TNeuron.cxx.

Referenced by TSynapse::SetPre(), and TSynapse::TSynapse().

void TNeuron::AddPre ( TSynapse * pre )

protected

Adds a synapse to the neuron as an input This method is used by the TSynapse while connecting two neurons.

Definition at line 834 of file TNeuron.cxx.

Referenced by TSynapse::SetPost(), and TSynapse::TSynapse().

Double_t TNeuron::DSigmoid ( Double_t x ) const

protected

The Derivative of the Sigmoid.

Definition at line 818 of file TNeuron.cxx.

Referenced by GetDerivative().

void TNeuron::ForceExternalValue ( Double_t value )

Uses the branch type to force an external value.

Definition at line 1125 of file TNeuron.cxx.

Referenced by TMultiLayerPerceptron::Evaluate().

Double_t TNeuron::GetBranch ( ) const

Returns the formula value.

Definition at line 914 of file TNeuron.cxx.

Referenced by TMultiLayerPerceptron::DrawResult(), GetError(), GetTarget(), and GetValue().

Double_t TNeuron::GetDeDw ( ) const

Computes the derivative of the error wrt the neuron weight.

Definition at line 1084 of file TNeuron.cxx.

Referenced by TMultiLayerPerceptron::ComputeDEDw(), TSynapse::GetDeDw(), GetDeDw(), and TMultiLayerPerceptron::MLP_Stochastic().

Double_t TNeuron::GetDEDw ( ) const

inline

Definition at line 76 of file TNeuron.h.

Referenced by TMultiLayerPerceptron::BFGSDir(), TMultiLayerPerceptron::ComputeDEDw(), TMultiLayerPerceptron::ConjugateGradientsDir(), TMultiLayerPerceptron::DerivDir(), TMultiLayerPerceptron::MLP_Batch(), TMultiLayerPerceptron::SetGammaDelta(), TMultiLayerPerceptron::SteepestDir(), and TMultiLayerPerceptron::Train().

Double_t TNeuron::GetDerivative ( ) const

computes the derivative for the appropriate function at the working point

Definition at line 1011 of file TNeuron.cxx.

Referenced by GetDeDw().

Double_t TNeuron::GetError ( ) const

Computes the error for output neurons.

Returns 0 for other neurons.

Definition at line 1063 of file TNeuron.cxx.

Referenced by GetDeDw(), and TMultiLayerPerceptron::GetSumSquareError().

TNeuron* TNeuron::GetInLayer ( Int_t n ) const

inline

Definition at line 60 of file TNeuron.h.

Referenced by TMultiLayerPerceptron::Export().

Double_t TNeuron::GetInput ( ) const

Returns neuron input.

Definition at line 925 of file TNeuron.cxx.

Referenced by GetDeDw(), and GetValue().

const Double_t* TNeuron::GetNormalisation ( ) const

inline

Definition at line 73 of file TNeuron.h.

Referenced by TMultiLayerPerceptron::DrawResult(), and TMultiLayerPerceptron::Export().

TSynapse* TNeuron::GetPost ( Int_t n ) const

inline

Definition at line 59 of file TNeuron.h.

TSynapse* TNeuron::GetPre ( Int_t n ) const

inline

Definition at line 58 of file TNeuron.h.

Referenced by TMultiLayerPerceptron::Export().

Double_t TNeuron::GetTarget ( ) const

Computes the normalized target pattern for output neurons.

Returns 0 for other neurons.

Definition at line 1074 of file TNeuron.cxx.

Referenced by TMultiLayerPerceptron::GetCrossEntropy(), and TMultiLayerPerceptron::GetCrossEntropyBinary().

TNeuron::ENeuronType TNeuron::GetType ( ) const

Returns the neuron type.

Definition at line 867 of file TNeuron.cxx.

Referenced by TMultiLayerPerceptron::Export().

Double_t TNeuron::GetValue ( ) const

Computes the output using the appropriate function and all the weighted inputs, or uses the branch as input.

In that case, the branch normalisation is also used.

Definition at line 948 of file TNeuron.cxx.

Referenced by TMultiLayerPerceptron::DrawResult(), TMultiLayerPerceptron::Evaluate(), TMultiLayerPerceptron::GetCrossEntropy(), TMultiLayerPerceptron::GetCrossEntropyBinary(), TSynapse::GetDeDw(), GetDerivative(), GetError(), TSynapse::GetValue(), and TMultiLayerPerceptron::Result().

Double_t TNeuron::GetWeight ( ) const

inline

Definition at line 71 of file TNeuron.h.

Referenced by TMultiLayerPerceptron::Export(), TMultiLayerPerceptron::LineSearch(), TMultiLayerPerceptron::MLP_Batch(), and TMultiLayerPerceptron::MLP_Stochastic().

TNeuron& TNeuron::operator= ( const TNeuron & )

private

void TNeuron::SetDEDw ( Double_t in )

Sets the derivative of the total error wrt the neuron weight.

Definition at line 1168 of file TNeuron.cxx.

Referenced by TMultiLayerPerceptron::ComputeDEDw().

void TNeuron::SetNewEvent ( ) const

Inform the neuron that inputs of the network have changed, so that the buffered values have to be recomputed.

Definition at line 1157 of file TNeuron.cxx.

Referenced by TMultiLayerPerceptron::Evaluate(), and TMultiLayerPerceptron::GetEntry().

void TNeuron::SetNormalisation	(	Double_t	mean,
		Double_t	RMS
	)

Sets the normalization variables.

Any input neuron will return (branch-mean)/RMS. When UseBranch is called, mean and RMS are automatically set to the actual branch mean and RMS.

Definition at line 1137 of file TNeuron.cxx.

Referenced by TMultiLayerPerceptron::AttachData(), and TMultiLayerPerceptron::LoadWeights().

void TNeuron::SetWeight ( Double_t w )

Sets the neuron weight to w.

The neuron weight corresponds to the bias in the linear combination of the inputs.

Definition at line 1148 of file TNeuron.cxx.

Referenced by TMultiLayerPerceptron::LoadWeights(), TMultiLayerPerceptron::MLP_Batch(), TMultiLayerPerceptron::MLP_Line(), TMultiLayerPerceptron::MLP_Stochastic(), and TMultiLayerPerceptron::Randomize().

Double_t TNeuron::Sigmoid ( Double_t x ) const

protected

The Sigmoid.

Fast computation of the values of the sigmoid function. Uses values of the function up to the seventh order tabulated at 700 points. Values were computed in long double precision (16 bytes, precision to about 37 digits) on a hp computer. Some values were checked with Mathematica. Result should be correct to ~ 15 digits (about double precision)

From the mlpfit package (J.Schwindling 20-Jul-1999)

Definition at line 95 of file TNeuron.cxx.

Referenced by GetValue().

TTreeFormula * TNeuron::UseBranch	(	TTree *	input,
		const char *	formula
	)

Sets a formula that can be used to make the neuron an input.

The formula is automatically normalized to mean=0, RMS=1. This normalisation is used by GetValue() (input neurons) and GetError() (output neurons)

Definition at line 878 of file TNeuron.cxx.

Referenced by TMultiLayerPerceptron::AttachData().

Friends And Related Function Documentation

friend class TSynapse

friend

Definition at line 49 of file TNeuron.h.

Member Data Documentation

Double_t TNeuron::fDeDw

private

do we need to compute fDeDw again ?

Definition at line 109 of file TNeuron.h.

Referenced by GetDeDw().

Double_t TNeuron::fDEDw

private

buffer containing the last derivative of the error

Definition at line 110 of file TNeuron.h.

Referenced by SetDEDw().

Double_t TNeuron::fDerivative

private

do we need to compute fDerivative again ?

Definition at line 107 of file TNeuron.h.

Referenced by GetDerivative().

TFormula* TNeuron::fExtD

private

Definition at line 97 of file TNeuron.h.

Referenced by GetDerivative().

TFormula* TNeuron::fExtF

private

Definition at line 96 of file TNeuron.h.

Referenced by GetValue().

TTreeFormula* TNeuron::fFormula

private

Definition at line 100 of file TNeuron.h.

Referenced by GetBranch(), and UseBranch().

Int_t TNeuron::fIndex

private

formula to be used for inputs and outputs

Definition at line 101 of file TNeuron.h.

Referenced by GetBranch(), and UseBranch().

Double_t TNeuron::fInput

private

do we need to compute fInput again ?

Definition at line 103 of file TNeuron.h.

Referenced by GetInput().

TObjArray TNeuron::flayer

private

Definition at line 92 of file TNeuron.h.

Referenced by AddInLayer(), and GetValue().

Bool_t TNeuron::fNewDeDw

private

buffer containing the last neuron derivative

Definition at line 108 of file TNeuron.h.

Referenced by GetDeDw().

Bool_t TNeuron::fNewDeriv

private

buffer containing the last neuron output

Definition at line 106 of file TNeuron.h.

Referenced by GetDerivative().

Bool_t TNeuron::fNewInput

private

index in the formula

Definition at line 102 of file TNeuron.h.

Referenced by GetInput().

Bool_t TNeuron::fNewValue

private

buffer containing the last neuron input

Definition at line 104 of file TNeuron.h.

Referenced by ForceExternalValue(), and GetValue().

Double_t TNeuron::fNorm[2]

private

Definition at line 94 of file TNeuron.h.

Referenced by ForceExternalValue(), GetError(), GetTarget(), GetValue(), SetNormalisation(), and UseBranch().

TObjArray TNeuron::fpost

private

Definition at line 91 of file TNeuron.h.

Referenced by AddPost(), GetDeDw(), GetError(), and GetTarget().

TObjArray TNeuron::fpre

private

Definition at line 90 of file TNeuron.h.

Referenced by AddPre(), GetDerivative(), GetInput(), and GetValue().

ENeuronType TNeuron::fType

private

Definition at line 95 of file TNeuron.h.

Referenced by GetDeDw(), GetDerivative(), GetType(), and GetValue().

Double_t TNeuron::fValue

private

do we need to compute fValue again ?

Definition at line 105 of file TNeuron.h.

Referenced by ForceExternalValue(), and GetValue().

Double_t TNeuron::fWeight

private

Definition at line 93 of file TNeuron.h.

Referenced by GetDerivative(), GetInput(), and SetWeight().

Collaboration diagram for TNeuron:

[legend]

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

tmva/tmva/inc/TMVA/TNeuron.h
math/mlp/src/TNeuron.cxx

Public Types

Public Member Functions

Protected Member Functions

Private Member Functions

Private Attributes

Friends

Additional Inherited Members

Member Enumeration Documentation

Constructor & Destructor Documentation

Member Function Documentation

Friends And Related Function Documentation

Member Data Documentation