CPerceptron Class Reference

Inheritance diagram for CPerceptron:

Inheritance graph
[legend]

List of all members.


Detailed Description

class Perceptron

Definition at line 20 of file Perceptron.h.


Public Member Functions

 CPerceptron ()
 CPerceptron (CRealFeatures *traindat, CLabels *trainlab)
virtual ~CPerceptron ()
virtual EClassifierType get_classifier_type ()
virtual bool train ()
void set_learn_rate (DREAL r)
 set learn rate of gradient descent training algorithm
void set_max_iter (INT i)
 set maximum number of iterations
virtual DREAL classify_example (INT vec_idx)
 get output for example "vec_idx"
void get_w (DREAL **dst_w, INT *dst_dims)
void set_w (DREAL *src_w, INT src_w_dim)
void set_bias (DREAL b)
DREAL get_bias ()
virtual bool load (FILE *srcfile)
virtual bool save (FILE *dstfile)
virtual CLabelsclassify (CLabels *output=NULL)
virtual void set_features (CRealFeatures *feat)
virtual CRealFeaturesget_features ()
virtual void set_labels (CLabels *lab)
virtual CLabelsget_labels ()
virtual DREAL get_label (INT i)
void set_max_train_time (DREAL t)
DREAL get_max_train_time ()

Static Public Attributes

static CParallel parallel
static CIO io
static CVersion version

Protected Attributes

DREAL learn_rate
INT max_iter
INT w_dim
DREALw
DREAL bias
CRealFeaturesfeatures
DREAL max_train_time
CLabelslabels

Constructor & Destructor Documentation

CPerceptron::CPerceptron (  ) 

default constructor

Definition at line 15 of file Perceptron.cpp.

CPerceptron::CPerceptron ( CRealFeatures traindat,
CLabels trainlab 
)

constructor

Parameters:
traindat training features
trainlab labels for training features

Definition at line 20 of file Perceptron.cpp.

CPerceptron::~CPerceptron (  )  [virtual]

Definition at line 27 of file Perceptron.cpp.


Member Function Documentation

virtual EClassifierType CPerceptron::get_classifier_type (  )  [virtual]

get classifier type

Returns:
classifier type PERCEPTRON

Reimplemented from CClassifier.

Definition at line 38 of file Perceptron.h.

bool CPerceptron::train (  )  [virtual]

train classifier

Returns:
if training was successful

Reimplemented from CClassifier.

Definition at line 31 of file Perceptron.cpp.

void CPerceptron::set_learn_rate ( DREAL  r  ) 

set learn rate of gradient descent training algorithm

Definition at line 47 of file Perceptron.h.

void CPerceptron::set_max_iter ( INT  i  ) 

set maximum number of iterations

Definition at line 53 of file Perceptron.h.

virtual DREAL CLinearClassifier::classify_example ( INT  vec_idx  )  [virtual, inherited]

get output for example "vec_idx"

Reimplemented from CClassifier.

Definition at line 30 of file LinearClassifier.h.

void CLinearClassifier::get_w ( DREAL **  dst_w,
INT dst_dims 
) [inherited]

get w

Parameters:
dst_w store w in this argument
dst_dims dimension of w

Definition at line 46 of file LinearClassifier.h.

void CLinearClassifier::set_w ( DREAL src_w,
INT  src_w_dim 
) [inherited]

set w

Parameters:
src_w new w
src_w_dim dimension of new w

Definition at line 61 of file LinearClassifier.h.

void CLinearClassifier::set_bias ( DREAL  b  )  [inherited]

set bias

Parameters:
b new bias

Definition at line 71 of file LinearClassifier.h.

DREAL CLinearClassifier::get_bias (  )  [inherited]

get bias

Returns:
bias

Definition at line 80 of file LinearClassifier.h.

bool CLinearClassifier::load ( FILE *  srcfile  )  [virtual, inherited]

load from file

Parameters:
srcfile file to load from
Returns:
if loading was successful

Reimplemented from CClassifier.

Definition at line 24 of file LinearClassifier.cpp.

bool CLinearClassifier::save ( FILE *  dstfile  )  [virtual, inherited]

save to file

Parameters:
dstfile file to save to
Returns:
if saving was successful

Reimplemented from CClassifier.

Definition at line 29 of file LinearClassifier.cpp.

CLabels * CLinearClassifier::classify ( CLabels output = NULL  )  [virtual, inherited]

classify all examples

Parameters:
output resulting labels
Returns:
resulting labels

Reimplemented from CClassifier.

Definition at line 34 of file LinearClassifier.cpp.

virtual void CLinearClassifier::set_features ( CRealFeatures feat  )  [virtual, inherited]

set features

Parameters:
feat features to set

Definition at line 110 of file LinearClassifier.h.

virtual CRealFeatures* CLinearClassifier::get_features (  )  [virtual, inherited]

get features

Returns:
features

Definition at line 121 of file LinearClassifier.h.

virtual void CClassifier::set_labels ( CLabels lab  )  [virtual, inherited]

set labels

Parameters:
lab labels

Definition at line 71 of file Classifier.h.

virtual CLabels* CClassifier::get_labels (  )  [virtual, inherited]

get labels

Returns:
labels

Definition at line 82 of file Classifier.h.

virtual DREAL CClassifier::get_label ( INT  i  )  [virtual, inherited]

get one specific label

Parameters:
i index of label to get
Returns:
value of label at index i

Definition at line 89 of file Classifier.h.

void CClassifier::set_max_train_time ( DREAL  t  )  [inherited]

set maximum training time

Parameters:
t maximimum training time

Definition at line 95 of file Classifier.h.

DREAL CClassifier::get_max_train_time (  )  [inherited]

get maximum training time

Returns:
maximum training time

Definition at line 101 of file Classifier.h.


Member Data Documentation

learning rate

Definition at line 60 of file Perceptron.h.

maximum number of iterations

Definition at line 62 of file Perceptron.h.

INT CLinearClassifier::w_dim [protected, inherited]

dimension of w

Definition at line 125 of file LinearClassifier.h.

DREAL* CLinearClassifier::w [protected, inherited]

w

Definition at line 127 of file LinearClassifier.h.

DREAL CLinearClassifier::bias [protected, inherited]

bias

Definition at line 129 of file LinearClassifier.h.

CRealFeatures* CLinearClassifier::features [protected, inherited]

features

Definition at line 131 of file LinearClassifier.h.

DREAL CClassifier::max_train_time [protected, inherited]

maximum training time

Definition at line 111 of file Classifier.h.

CLabels* CClassifier::labels [protected, inherited]

labels

Definition at line 114 of file Classifier.h.

CParallel CSGObject::parallel [static, inherited]

Definition at line 105 of file SGObject.h.

CIO CSGObject::io [static, inherited]

Definition at line 106 of file SGObject.h.

CVersion CSGObject::version [static, inherited]

Definition at line 107 of file SGObject.h.


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

SHOGUN Machine Learning Toolbox - Documentation