C# Class Ocronet.Dynamic.Recognizers.MlpClassifier

Inheritance: IBatchDense

ファイルを表示 Open project: nickun/OCRonet Class Usage Examples

Protected Properties

Property	Type	Description
crossvalidate	bool
cv_error	float
nn_error	float
personal_number	int
w1	Floatarray

Public Methods

Method	Description
ChangeHidden ( int newn ) : void
Complexity ( ) : float
Copy ( MlpClassifier other ) : void
CrossValidatedError ( ) : float
Info ( ) : void
InitData ( IDataset ds, int nhidden, Intarray newc2i = null, Intarray newi2c = null ) : void
MlpClassifier ( ) : System
MlpClassifier ( int PersonalNumber ) : System
OutputsDense ( Floatarray result, Floatarray x_raw ) : float
TrainDense ( IDataset ds ) : void
TrainOne ( Floatarray z, Floatarray target, Floatarray x, float eta ) : void	do a single stochastic gradient descent step
dsigmoidy ( float y ) : float
dstdsigmoid ( float x ) : float	derivative of the "standard" sigmoid
nClasses ( ) : int
nFeatures ( ) : int
nHidden ( ) : int
sigmoid ( float x ) : float	sigmoid function for neural networks 0 .. 1
sigmoid_speed ( float x ) : float	"standard" sigmoid -1.71593428 .. 1.71593428

Protected Methods

Method	Description
InitRandom ( int ninput, int nhidden, int noutput ) : void
count_zeros ( Floatarray a ) : int
logspace ( int i, int n, float lo, float hi ) : float	logarithmically spaced samples in an interval
mvmul0 ( Floatarray result, Floatarray a, Floatarray v ) : void	random samples from the normal density
normalize ( Floatarray v ) : void
outer_add ( Floatarray a, Floatarray u, Floatarray v, float eps ) : void
vmmul0 ( Floatarray result, Floatarray v, Floatarray a ) : void

Method Details

ChangeHidden() public method

public ChangeHidden ( int newn ) : void
newn	int
return	void

Complexity() public method

public Complexity ( ) : float
return	float

Copy() public method

public Copy ( MlpClassifier other ) : void
other	MlpClassifier
return	void

CrossValidatedError() public method

public CrossValidatedError ( ) : float
return	float

Info() public method

public Info ( ) : void
return	void

InitData() public method

public InitData ( IDataset ds, int nhidden, Intarray newc2i = null, Intarray newi2c = null ) : void
ds	Ocronet.Dynamic.IOData.IDataset
nhidden	int
newc2i	Intarray
newi2c	Intarray
return	void

InitRandom() protected method

protected InitRandom ( int ninput, int nhidden, int noutput ) : void
ninput	int
nhidden	int
noutput	int
return	void

MlpClassifier() public method

public MlpClassifier ( ) : System
return	System

MlpClassifier() public method

public MlpClassifier ( int PersonalNumber ) : System
PersonalNumber	int
return	System

OutputsDense() public method

public OutputsDense ( Floatarray result, Floatarray x_raw ) : float
result	Floatarray
x_raw	Floatarray
return	float

TrainDense() public method

public TrainDense ( IDataset ds ) : void
ds	Ocronet.Dynamic.IOData.IDataset
return	void

TrainOne() public method

do a single stochastic gradient descent step

public TrainOne ( Floatarray z, Floatarray target, Floatarray x, float eta ) : void
z	Floatarray
target	Floatarray
x	Floatarray
eta	float
return	void

count_zeros() protected static method

protected static count_zeros ( Floatarray a ) : int
a	Floatarray
return	int

dsigmoidy() public static method

public static dsigmoidy ( float y ) : float
y	float
return	float

dstdsigmoid() public static method

derivative of the "standard" sigmoid

public static dstdsigmoid ( float x ) : float
x	float
return	float

logspace() protected static method

logarithmically spaced samples in an interval

protected static logspace ( int i, int n, float lo, float hi ) : float
i	int
n	int
lo	float
hi	float
return	float

mvmul0() protected static method

random samples from the normal density

protected static mvmul0 ( Floatarray result, Floatarray a, Floatarray v ) : void
result	Floatarray
a	Floatarray
v	Floatarray
return	void

nClasses() public method

public nClasses ( ) : int
return	int

nFeatures() public method

public nFeatures ( ) : int
return	int

nHidden() public method

public nHidden ( ) : int
return	int

normalize() protected method

protected normalize ( Floatarray v ) : void
v	Floatarray
return	void

outer_add() protected static method

protected static outer_add ( Floatarray a, Floatarray u, Floatarray v, float eps ) : void
a	Floatarray
u	Floatarray
v	Floatarray
eps	float
return	void

sigmoid() public static method

sigmoid function for neural networks 0 .. 1

public static sigmoid ( float x ) : float
x	float
return	float

sigmoid_speed() public static method

"standard" sigmoid -1.71593428 .. 1.71593428

public static sigmoid_speed ( float x ) : float
x	float
return	float

vmmul0() protected static method

protected static vmmul0 ( Floatarray result, Floatarray v, Floatarray a ) : void
result	Floatarray
v	Floatarray
a	Floatarray
return	void

Property Details

crossvalidate protected_oe property

protected bool crossvalidate
return	bool

cv_error protected_oe property

protected float cv_error
return	float

nn_error protected_oe property

protected float nn_error
return	float

personal_number protected_oe property

protected int personal_number
return	int

w1 protected_oe property

protected Floatarray w1
return	Floatarray