From f77a4937a5f09d1f49a114ada70b9e11be44b1d6 Mon Sep 17 00:00:00 2001
From: Joe Zhao <ztuowen@gmail.com>
Date: Sun, 31 May 2015 15:10:15 +0800
Subject: misc

---
 model/rankaccu.cpp  |  3 +--
 model/ranksvm.cpp   | 10 +++++-----
 model/ranksvmtn.cpp | 24 +++++++++++++++---------
 train.cpp           |  2 +-
 4 files changed, 22 insertions(+), 17 deletions(-)

diff --git a/model/rankaccu.cpp b/model/rankaccu.cpp
index fc5b7b7..8404abf 100644
--- a/model/rankaccu.cpp
+++ b/model/rankaccu.cpp
@@ -108,12 +108,11 @@ void rank_accu(RidList &D,const vector<double> pred)
 
 void rank_CMC(RidList &D,const std::vector<double> pred,CMC & cmc) {
     unsigned long n = D.getSize();
-    vector<int> orig_rank(n),pred_rank(n);
+    vector<int> pred_rank(n);
     vector<double> orig(n);
     int i,j;
     for (i=0;i<D.getSize();++i)
     {
-        orig_rank[i]=i;
         pred_rank[i]=i;
         orig[i]=D.getL(i);
     }
diff --git a/model/ranksvm.cpp b/model/ranksvm.cpp
index 368e16d..d246b2b 100644
--- a/model/ranksvm.cpp
+++ b/model/ranksvm.cpp
@@ -12,14 +12,14 @@ double C=1e-4;// Compensating & scaling
 
 // Main terminating criteria
 int maxiter = 1; // max iteration count
-double prec=1e-10; // precision
+double prec=1e-15; // precision
 // conjugate gradient
-double cg_prec=1e-10; // precision
-int cg_maxiter = 100;
+double cg_prec=1e-20; // precision
+int cg_maxiter = 1000;
 int ls_maxiter = 20;
 // line search
-double ls_prec=1e-10; // precision
-double ls_turb=1e-15; // purturbation
+double ls_prec=1e-20; // precision
+double ls_turb=1e-30; // purturbation
 
 
 int RSVM::saveModel(const string fname){
diff --git a/model/ranksvmtn.cpp b/model/ranksvmtn.cpp
index 4572484..15a5e10 100644
--- a/model/ranksvmtn.cpp
+++ b/model/ranksvmtn.cpp
@@ -6,6 +6,8 @@
 using namespace std;
 using namespace Eigen;
 
+double RC=0;
+
 void cal_Dw(RidList &D,const VectorXd &w, VectorXd &Dw)
 {
     int n = D.getSize();
@@ -63,7 +65,7 @@ int cal_Hs(RidList &D,const vector<int> &rank,const VectorXd &corr,const VectorX
         tmp(i) = alpha(i)*Ds(i)-gamma(i);
     VectorXd res = VectorXd::Zero(D.getfSize());
     cal_Dtw(D,tmp,res);
-    Hs = s + C*res;
+    Hs = s + RC*res;
     return 0;
 }
 
@@ -188,7 +190,7 @@ int line_search(const VectorXd &w,RidList &D,const VectorXd &corr,const VectorXd
         VectorXd tmp = alpha.cwiseProduct(yt)-beta;
         VectorXd res = VectorXd::Zero(D.getfSize());
         cal_Dtw(D,tmp,res);
-        grad = grad + C*res;
+        grad = grad + RC*res;
         g = grad.dot(step);
         cal_Hs(D,rank,corr,alpha,step,Hs);
         h = Hs.dot(step);
@@ -216,7 +218,7 @@ int train_orig(int fsize, RidList &Data,const VectorXd &corr,VectorXd &weight){
     VectorXd grad(fsize);
     VectorXd step(fsize);
     vector<int> rank(n);
-    double obj,t;
+    double obj,t,l;
 
     VectorXd dw(n);
     VectorXd yt;
@@ -227,11 +229,12 @@ int train_orig(int fsize, RidList &Data,const VectorXd &corr,VectorXd &weight){
         cal_Dw(Data,weight,dw);
         cal_alpha_beta(dw,corr,Data,rank,yt,alpha,beta);
         // Generate support vector matrix sv & gradient
-        obj = (weight.dot(weight) + C*(alpha.dot(yt.cwiseProduct(yt))-beta.dot(yt)))/2;
+        l=alpha.dot(yt.cwiseProduct(yt))-beta.dot(yt);
+        obj = (weight.dot(weight) + RC*l)/2;
         VectorXd tmp = alpha.cwiseProduct(yt)-beta;
         VectorXd res = VectorXd::Zero(fsize);
         cal_Dtw(Data,tmp,res);
-        grad = weight + C*res;
+        grad = weight + RC*res;
         // Solve
         cg_solve(Data,rank,corr,alpha,grad,step);
         // do line search
@@ -240,7 +243,7 @@ int train_orig(int fsize, RidList &Data,const VectorXd &corr,VectorXd &weight){
         // When dec is small enough
         double nprec = step.dot(grad)/obj;
         ++iter;
-        LOG(INFO)<<"Iter: "<<iter<<" Obj: " <<obj << " Ndec/Obj:"<<nprec << " linesearch: "<< -t ;
+        LOG(INFO)<<"Iter: "<<iter<<" Obj: " <<obj<< " l: "<< l << " Ndec/Obj:"<<nprec << " linesearch: "<< -t ;
         if (iter>= maxiter)
         {
             LOG(INFO)<< "Maxiter reached";
@@ -254,11 +257,11 @@ int train_orig(int fsize, RidList &Data,const VectorXd &corr,VectorXd &weight){
 
 int RSVMTN::train(RidList &D){
     VectorXd corr(D.getSize());
-    vector<int> A1,A2;
-    int i,j;
+    int i;
     LOG(INFO)<<"Processing input";
     for (i=0;i<D.getSize();++i)
         corr(i)=D.getL(i)>0?0.5:-0.5;
+    RC=2.0*C;
     train_orig(fsize,D,corr,model.weight);
     return 0;
 };
@@ -267,6 +270,9 @@ int RSVMTN::predict(RidList &D, vector<double> &res){
     res.clear();
     int n = D.getSize();
     for (int i=0;i<n;++i)
-        res.push_back(D.getVecDot(i,model.weight));
+    {
+        double r=D.getVecDot(i,model.weight);
+        res.push_back(r);
+    }
     return 0;
 };
\ No newline at end of file
diff --git a/train.cpp b/train.cpp
index 07f9edc..1c49902 100644
--- a/train.cpp
+++ b/train.cpp
@@ -28,7 +28,7 @@ int train(DataProvider &dp) {
     dp.getAllDataSet(D);
     LOG(INFO)<<"Read "<<D.getSize()<<" entries with "<< D.getfSize()<<" features";
     LOG(INFO)<<"C: "<<C<<" ,iter: "<<maxiter<<" ,prec: "<<prec;
-    LOG(INFO)<<"cg_maxiter: "<<cg_maxiter<<" ,cg_prec:"<<cg_prec<<" ,ls_maxiter: "<<ls_maxiter<<" ,ls_prec: "<<ls_prec;
+    LOG(INFO)<<"cg_maxiter: "<<cg_maxiter<<" ,cg_prec: "<<cg_prec<<" ,ls_maxiter: "<<ls_maxiter<<" ,ls_prec: "<<ls_prec;
 
     rsvm->train(D);
 
-- 
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