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sebastic-guest pushed a commit to branch upstream-master
in repository pktools.
commit 5177b231d0e92f1f0f5666aeda2ff662a6f3120b
Author: Pieter Kempeneers <kempe...@gmail.com>
Date: Mon Jun 23 22:53:04 2014 +0200
working on pkfssvm, linking, but not correctly working
---
src/algorithms/CostFactory.h | 7 ++++---
src/apps/pkfssvm.cc | 47 +++++++++++---------------------------------
2 files changed, 16 insertions(+), 38 deletions(-)
diff --git a/src/algorithms/CostFactory.h b/src/algorithms/CostFactory.h
index 982e9dc..e85aad8 100644
--- a/src/algorithms/CostFactory.h
+++ b/src/algorithms/CostFactory.h
@@ -30,8 +30,9 @@ along with pktools. If not, see
<http://www.gnu.org/licenses/>.
class CostFactory{
public:
CostFactory(void){};
- CostFactory(unsigned short cv, short verbose) : m_cv(cv),
m_verbose(verbose){};
- virtual ~CostFactory(void);
+ CostFactory(unsigned short cv, short verbose) : m_cv(cv),
m_verbose(verbose){};
+
+ virtual ~CostFactory(void){};
void setCv(unsigned short cv){m_cv=cv;};
void setClassValueMap(const std::string& classname, short classvalue){
m_classValueMap[classname]=classvalue;};
std::map<std::string,short> getClassValueMap(){return m_classValueMap;};
@@ -43,7 +44,7 @@ public:
void setNcTraining(const std::vector<unsigned int>
nctraining){m_nctraining=nctraining;};
void setNcTest(const std::vector<unsigned int> nctest){m_nctest=nctest;};
//getCost needs to be implemented case by case (e.g., SVM, ANN)
- virtual double getCost(const std::vector<Vector2d<float> >
&trainingFeatures);
+ virtual double getCost(const std::vector<Vector2d<float> >
&trainingFeatures){};
protected:
ConfusionMatrix m_cm;
diff --git a/src/apps/pkfssvm.cc b/src/apps/pkfssvm.cc
index 20818b1..6daeb8e 100644
--- a/src/apps/pkfssvm.cc
+++ b/src/apps/pkfssvm.cc
@@ -28,48 +28,16 @@ along with pktools. If not, see
<http://www.gnu.org/licenses/>.
#include "algorithms/FeatureSelector.h"
#include "algorithms/svm.h"
#include "imageclasses/ImgReaderOgr.h"
+#include "pkfssvm.h"
#ifdef HAVE_CONFIG_H
#include <config.h>
#endif
-namespace svm{
- enum SVM_TYPE {C_SVC=0, nu_SVC=1,one_class=2, epsilon_SVR=3, nu_SVR=4};
- enum KERNEL_TYPE {linear=0,polynomial=1,radial=2,sigmoid=3};
-}
-
-enum SelectorValue { NA=0, SFFS=1, SFS=2, SBS=3, BFS=4 };
-
using namespace std;
#define Malloc(type,n) (type *)malloc((n)*sizeof(type))
-class CostFactorySVM : public CostFactory
-{
-public:
- CostFactorySVM()
- : CostFactory(2,0), m_svm_type("C_SVC"), m_kernel_type("radial"),
m_kernel_degree(3), m_gamma(1.0), m_coef0(0), m_ccost(1000), m_nu(0.5),
m_epsilon_loss(100), m_cache(100), m_epsilon_tol(0.001), m_shrinking(false),
m_prob_est(true){};
- // ~CostFactorySVM(){};
- CostFactorySVM(std::string svm_type, std::string kernel_type, unsigned short
kernel_degree, float gamma, float coef0, float ccost, float nu, float
epsilon_loss, int cache, float epsilon_tol, bool shrinking, bool prob_est,
unsigned short cv, bool verbose)
- : CostFactory(cv,verbose), m_svm_type(svm_type),
m_kernel_type(kernel_type), m_kernel_degree(kernel_degree), m_gamma(gamma),
m_coef0(coef0), m_ccost(ccost), m_nu(nu), m_epsilon_loss(epsilon_loss),
m_cache(cache), m_epsilon_tol(epsilon_tol), m_shrinking(shrinking),
m_prob_est(prob_est){};
- ~CostFactorySVM();
- double getCost(const vector<Vector2d<float> > &trainingFeatures);
-
-private:
- string m_svm_type;
- string m_kernel_type;
- unsigned short m_kernel_degree;
- float m_gamma;
- float m_coef0;
- float m_ccost;
- float m_nu;
- float m_epsilon_loss;
- int m_cache;
- float m_epsilon_tol;
- bool m_shrinking;
- bool m_prob_est;
-};
-
//global parameters used in cost function getCost
// ConfusionMatrix cm;
// map<string,short> classValueMap;
@@ -77,8 +45,17 @@ private:
// vector<unsigned int> nctraining;
// vector<unsigned int> nctest;
-double CostFactorySVM::getCost(const vector<Vector2d<float> >
&trainingFeatures)
-{
+CostFactorySVM::CostFactorySVM()
+ : CostFactory(2,0), m_svm_type("C_SVC"), m_kernel_type("radial"),
m_kernel_degree(3), m_gamma(1.0), m_coef0(0), m_ccost(1000), m_nu(0.5),
m_epsilon_loss(100), m_cache(100), m_epsilon_tol(0.001), m_shrinking(false),
m_prob_est(true){
+}
+
+CostFactorySVM::~CostFactorySVM(){
+}
+
+CostFactorySVM::CostFactorySVM(std::string svm_type, std::string kernel_type,
unsigned short kernel_degree, float gamma, float coef0, float ccost, float nu,
float epsilon_loss, int cache, float epsilon_tol, bool shrinking, bool
prob_est, unsigned short cv, bool verbose)
+ : CostFactory(cv,verbose), m_svm_type(svm_type),
m_kernel_type(kernel_type), m_kernel_degree(kernel_degree), m_gamma(gamma),
m_coef0(coef0), m_ccost(ccost), m_nu(nu), m_epsilon_loss(epsilon_loss),
m_cache(cache), m_epsilon_tol(epsilon_tol), m_shrinking(shrinking),
m_prob_est(prob_est){};
+
+double CostFactorySVM::getCost(const vector<Vector2d<float> >
&trainingFeatures){
std::map<std::string, svm::SVM_TYPE> svmMap;
svmMap["C_SVC"]=svm::C_SVC;
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