libtinysvm Reference Manual

Last update: $Date: 2000/12/08 18:39:42 $

List of Contents

• Class Reference Manual
  • Param class
  • BaseExample class
  • Example class
  • Model class
• Sample Programming
• How to compile

Class Reference Manual

class Param
{
public:
  int set (int,  char **);
  int set (const char *);
};

Param::set (int argc, char **argv)

Set parameter with argc, argv style, --- arguments for main() function.
This function accepts same parameter used for svm_learn.

Param::set (const char *s)

Set parameter with string s, e.g."-t 1 -d 3 -c 1".
This function accepts same parameter used for svm_learn.

class BaseExample
{
public:
  int          l;
  double       *y;    
  feature_node **x;

  int add (const double, feature_node *);
  int add (const double, const char *);
  int add (const char *);
  int clear ();
  int size ();

  virtual int read  (const char *, const char *mode = "r", int offset = 0) = 0;
  virtual int write (const char *, const char *mode = "w", int offset = 0) = 0;
};

BaseExample is a base class for Example and Model. You need not use this class directory.

BaseExample::add (const double y, feature_node *x)

Add new example y and x into current instance.
Return 1 if success, return 0 if fail.

BaseExample::add (const double y, char *x)

Add new example y and x into current instance. x is represented with a string , e.g. "1:2 3:4 5:6".
Return 1 if success, return 0 if fail.

BaseExample::add (char *s)

Add new example represented with single string, e.g. "+1 1:2 3:4 5:1" into current instance.
Return 1 if success, return 0 if fail.

BaseExample::clear ()

Clear all examples (pair of y and x) stored in current instance.

BaseExample::size ()

Get the size of examples (pair of y and x).

BaseExample::read (const char *file_name, const char *mode ="r", int offset = 0)

Add all examples stored in file_name into current instance, mode is used for calling fopen (3).
if offset is given, seek offset byte using fseek (3) before reading stored examples.
Return 1 if success, return 0 if fail.

BaseExample::write (const char *file_name, const char *mode ="w", int offset = 0)

Save all stored examples into file_name. mode is used for calling fopen(3).
By setting "a" to mode, you can append examples into file_name.
offset is reserved argument for the future.
Return 1 if success, return 0 if fail.

class Example: public BaseExample
{
public:
  Model *learn (const Param &);
  Model *learn (const char *);
};

Example class is inherited from BaseExample class. You can use all member functions defined in BaseExample class.

Example::learn (const Param &p)

Execute learning with Param object p.
Return new instance (pointer) of Model object.

Example::learn (const char *s)

Execute learning with Parameter represented with single string s, e.g. "-t 1 -d 2 -c 1".
Return new instance (pointer) of Model object.

class Model: public BaseExample
{
 public:
  double b;
  int    bsv;
  int    *svindex;

  Model ();
  Model (const Param &);

  int writeSVindex (const char *, const char *mode = "r", int offset = 0);

  double classify (const char *);
  double classify (const feature_node *);
  double estimateMargin ();
  double estimateVC ();

  int getSVnum ();
  const int *getSVindex ();

};

Model class is inherited from BaseExample class. You can use all member functions defined in BaseExample class.

Model::Model* (const Param &p)

Create new Model instance with Param object p.

Model::classify (const char *s)

Classify test example represented with single string s, e.g. "1:1 2:1 3:1".
Return distance from the decision hyperplane.

Model::classify (const feature_node *f)

Classify test example represented with feature_node "f".
Return distance from the decision hyper plane.

Model::writeSVindex (const char *file_name const char *mode = "w", int offset = 0)

Write index of Support Vectors and weight y into file_name.
This method can be used when current instance is created by the Example::learn () method.

Model::estimateMargin ()

Return the estimated margin value

Model::estimateVC ()

Return the estimated VC dimension. This value is roughly approximated.

Model::getSVnum ()

Return the number of Support Vectors

Model::getSVindex ()

Return the pointer of Index of Support Vectors.
This method can be used when current instance is created by the Example::learn () method.

Sample Programming

• Leaning with file-name, and store the result into model-file.

  #include <tinysvm.h>
  
     Example e;
     Param p;
  
     if (! e.read(file-name)) throw;
     if (! p.set("-t 1 -d 2 -c 1")) throw;
  
     Model *m = e.learn(p);
  
     m->write(model-file);
  
     delete m;
  

• Classifying using stored model-file

  #include <tinysvm.h>
  
     Model m;
  
     if (! m.read(model-file)) throw;
  
     cout << m.classify("1:1 2:1 3:1 4:1") << endl;
  
  

• svm_learn, svm_classify and svm_model, all of these included program are written with libtinysvm.
  I think these sources would also help you to build your own programs.

How to compile

c++ -I/usr/local/include -L/usr/local/lib sample.cc -o sample -ltinysvm

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