scaffolding

3 files changed, 18 insertions, 5 deletions

diff --git a/model/ranksvm.h b/model/ranksvm.h
index e7b7c4a..21fb30b 100644
--- a/model/ranksvm.h
+++ b/model/ranksvm.h
@@ -12,8 +12,10 @@ protected:
     Eigen::VectorXd model;
     int fsize;
 public:
-    virtual int train(DataProvider &D)=0; // Dataprovider will have to provide label
-    virtual int predict(DataProvider &D)=0;  // TODO Not sure how to construct this
+    virtual int train(DataSet &D, Labels &label)=0;
+    virtual int predict(DataSet &D, Eigen::MatrixXd &res)=0;
+    // TODO Not sure how to construct this
+    //  Possible solution: generate a nxn matrix each row contains the sorted list of ranker result.
     int saveModel(const std::string fname);
     static RSVM* loadModel(const std::string fname);
     virtual std::string getName()=0;
diff --git a/model/ranksvmtn.cpp b/model/ranksvmtn.cpp
new file mode 100644
index 0000000..ef8d98c
--- /dev/null
+++ b/model/ranksvmtn.cpp
@@ -0,0 +1,12 @@
+#include "ranksvmtn.h"
+
+using namespace std;
+using namespace Eigen;
+
+int RSVMTN::train(DataSet &D, Labels &label){
+    return 0;
+};
+
+int RSVMTN::predict(DataSet &D, MatrixXd &res){
+    return 0;
+};
\ No newline at end of file
diff --git a/model/ranksvmtn.h b/model/ranksvmtn.h
index 4a0fb16..21b03bd 100644
--- a/model/ranksvmtn.h
+++ b/model/ranksvmtn.h
@@ -12,9 +12,8 @@ public:
     {
         return "TN";
     };
-
-    int train(DataProvider &D){return 0;};
-    int predict(DataProvider &D){return 0;};
+    virtual int train(DataSet &D, Labels &label);
+    virtual int predict(DataSet &D, Eigen::MatrixXd &res);
 };
 
 #endif
\ No newline at end of file