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VwExample Class Reference

Detailed Description

Example class for VW.

It contains a label object pointer. These objects should be returned by the parser.

Definition at line 58 of file vw_example.h.

Public Member Functions

 VwExample ()
 ~VwExample ()
void reset_members ()

Public Attributes

VwLabelld
 Label object.
v_array< char > tag
 Tag.
v_array< vw_size_tindices
 Array of namespaces.
v_array< VwFeatureatomics [256]
 Array of features.
vw_size_t num_features
 Number of features.
vw_size_t pass
 Pass.
float32_t final_prediction
 Final prediction.
float32_t loss
 Loss.
float32_t eta_round
 Learning rate for this round.
float32_t global_weight
 Global weight.
float32_t example_t
 t value for this example
float64_t sum_feat_sq [256]
 Sum of square of features.
float32_t total_sum_feat_sq
 Total sum of square of features.
vw_size_t example_counter
 Example counter.
bool sorted
 Whether features are sorted by weight index.

Constructor & Destructor Documentation

VwExample ( )

Constructor

Definition at line 19 of file vw_example.cpp.

~VwExample ( )

Destructor

Definition at line 28 of file vw_example.cpp.

Member Function Documentation

void reset_members ( )

Resets the members so the values can be updated directly without constructing another object.

Definition at line 34 of file vw_example.cpp.

Member Data Documentation

v_array<VwFeature> atomics[256]

Array of features.

Definition at line 86 of file vw_example.h.

float32_t eta_round

Learning rate for this round.

Definition at line 97 of file vw_example.h.

vw_size_t example_counter

Example counter.

Definition at line 109 of file vw_example.h.

float32_t example_t

t value for this example

Definition at line 101 of file vw_example.h.

float32_t final_prediction

Final prediction.

Definition at line 93 of file vw_example.h.

float32_t global_weight

Global weight.

Definition at line 99 of file vw_example.h.

v_array<vw_size_t> indices

Array of namespaces.

Definition at line 84 of file vw_example.h.

VwLabel* ld

Label object.

Definition at line 79 of file vw_example.h.

float32_t loss

Loss.

Definition at line 95 of file vw_example.h.

vw_size_t num_features

Number of features.

Definition at line 89 of file vw_example.h.

vw_size_t pass

Pass.

Definition at line 91 of file vw_example.h.

bool sorted

Whether features are sorted by weight index.

Definition at line 111 of file vw_example.h.

float64_t sum_feat_sq[256]

Sum of square of features.

Definition at line 104 of file vw_example.h.

v_array<char> tag

Tag.

Definition at line 82 of file vw_example.h.

float32_t total_sum_feat_sq

Total sum of square of features.

Definition at line 106 of file vw_example.h.


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

SHOGUN Machine Learning Toolbox - Documentation