Algorithm-SVM

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bindings.h  view on Meta::CPAN

#include "libsvm.h"

class DataSet {
  friend class SVM;

 private:
  double label;
  struct svm_node *attributes;
	int n; int max_n; int max_i;
	bool realigned;
 public:
  DataSet(double l);
  void   setLabel(double l) { label = l; }
  double getLabel() { return label; }
	int getMaxI() { return max_i; }
  void   setAttribute(int k, double v);
  double getAttribute(int k);
	int    getIndexAt(int i) { if (i<=n) { return attributes[i].index; } else { return -1; }}
	double getValueAt(int i) { if (i<=n) { return attributes[i].value; } else { return 0; }}

	void realign(struct svm_node *address);
  ~DataSet();
};


class SVM {
 public:
  SVM(int st, int kt, int d, double g, double c0, double C, double nu,
      double e);
  void   addDataSet(DataSet *ds);
  int    saveModel(char *filename);
  int    loadModel(char *filename);
  void   clearDataSet();
  int    train(int retrain);
  double predict_value(DataSet *ds);
  double predict(DataSet *ds);
	void   free_x_space();

libsvm.cpp  view on Meta::CPAN

#endif

//
// Kernel Cache
//
// l is the number of total data items
// size is the cache size limit in bytes
//
class Cache
{
public:
	Cache(int l,long int size);
	~Cache();

	// request data [0,len)
	// return some position p where [p,len) need to be filled
	// (p >= len if nothing needs to be filled)
	int get_data(const int index, Qfloat **data, int len);
	void swap_index(int i, int j);	// future_option
private:
	int l;

libsvm.cpp  view on Meta::CPAN

}

//
// Kernel evaluation
//
// the static method k_function is for doing single kernel evaluation
// the constructor of Kernel prepares to calculate the l*l kernel matrix
// the member function get_Q is for getting one column from the Q Matrix
//
class QMatrix {
public:
	virtual Qfloat *get_Q(int column, int len) const = 0;
	virtual Qfloat *get_QD() const = 0;
	virtual void swap_index(int i, int j) const = 0;
	virtual ~QMatrix() {}
};

class Kernel: public QMatrix {
public:
	Kernel(int l, svm_node * const * x, const svm_parameter& param);
	virtual ~Kernel();

	static double k_function(const svm_node *x, const svm_node *y,
				 const svm_parameter& param);
	virtual Qfloat *get_Q(int column, int len) const = 0;
	virtual Qfloat *get_QD() const = 0;
	virtual void swap_index(int i, int j) const	// no so const...
	{
		swap(x[i],x[j]);

libsvm.cpp  view on Meta::CPAN

//
// Given:
//
//	Q, p, y, Cp, Cn, and an initial feasible point \alpha
//	l is the size of vectors and matrices
//	eps is the stopping tolerance
//
// solution will be put in \alpha, objective value will be put in obj
//
class Solver {
public:
	Solver() {};
	virtual ~Solver() {};

	struct SolutionInfo {
		double obj;
		double rho;
		double upper_bound_p;
		double upper_bound_n;
		double r;	// for Solver_NU
	};

libsvm.cpp  view on Meta::CPAN

		r = (ub+lb)/2;

	return r;
}

//
// Solver for nu-svm classification and regression
//
// additional constraint: e^T \alpha = constant
//
class Solver_NU : public Solver
{
public:
	Solver_NU() {}
	void Solve(int l, const QMatrix& Q, const double *p, const schar *y,
		   double *alpha, double Cp, double Cn, double eps,
		   SolutionInfo* si, int shrinking)
	{
		this->si = si;
		Solver::Solve(l,Q,p,y,alpha,Cp,Cn,eps,si,shrinking);
	}
private:
	SolutionInfo *si;

libsvm.cpp  view on Meta::CPAN

	else
		r2 = (ub2+lb2)/2;
	
	si->r = (r1+r2)/2;
	return (r1-r2)/2;
}

//
// Q matrices for various formulations
//
class SVC_Q: public Kernel
{ 
public:
	SVC_Q(const svm_problem& prob, const svm_parameter& param, const schar *y_)
	:Kernel(prob.l, prob.x, param)
	{
		clone(y,y_,prob.l);
		cache = new Cache(prob.l,(long int)(param.cache_size*(1<<20)));
		QD = new Qfloat[prob.l];
		for(int i=0;i<prob.l;i++)
			QD[i]= (Qfloat)(this->*kernel_function)(i,i);
	}
	

libsvm.cpp  view on Meta::CPAN

		delete[] y;
		delete cache;
		delete[] QD;
	}
private:
	schar *y;
	Cache *cache;
	Qfloat *QD;
};

class ONE_CLASS_Q: public Kernel
{
public:
	ONE_CLASS_Q(const svm_problem& prob, const svm_parameter& param)
	:Kernel(prob.l, prob.x, param)
	{
		cache = new Cache(prob.l,(long int)(param.cache_size*(1<<20)));
		QD = new Qfloat[prob.l];
		for(int i=0;i<prob.l;i++)
			QD[i]= (Qfloat)(this->*kernel_function)(i,i);
	}
	
	Qfloat *get_Q(int i, int len) const

libsvm.cpp  view on Meta::CPAN

	~ONE_CLASS_Q()
	{
		delete cache;
		delete[] QD;
	}
private:
	Cache *cache;
	Qfloat *QD;
};

class SVR_Q: public Kernel
{ 
public:
	SVR_Q(const svm_problem& prob, const svm_parameter& param)
	:Kernel(prob.l, prob.x, param)
	{
		l = prob.l;
		cache = new Cache(l,(long int)(param.cache_size*(1<<20)));
		QD = new Qfloat[2*l];
		sign = new schar[2*l];
		index = new int[2*l];
		for(int k=0;k<l;k++)
		{