Fixes for MALSAR JFL

shogun-toolbox · Jul 25, 2012 · 09b53b5 · 09b53b5
1 parent 086ee0a
commit 09b53b5
Showing 1 changed file with 15 additions and 19 deletions.
diff --git a/src/shogun/lib/malsar/malsar_joint_feature_learning.cpp b/src/shogun/lib/malsar/malsar_joint_feature_learning.cpp
@@ -15,6 +15,7 @@
 #include <iostream>
 
 using namespace Eigen;
+using namespace std;
 
 namespace shogun
 {
@@ -39,21 +40,6 @@ malsar_result_t malsar_joint_feature_learning(
 	// initialize weight vector and bias for each task
 	MatrixXd Ws = MatrixXd::Zero(n_feats, n_tasks);
 	VectorXd Cs = VectorXd::Zero(n_tasks);
-	for (task=0; task<n_tasks; task++)
-	{
-		int n_pos = 0;
-		int n_neg = 0;
-		SGVector<index_t> task_idx = options.tasks_indices[task];
-		for (int i=0; i<task_idx.vlen; i++)
-		{
-			if (y[task_idx[i]] > 0)
-				n_pos++;
-			else
-				n_neg++;
-		}
-		Cs[task] = CMath::log(double(n_pos)/n_neg);
-	}
-
 	MatrixXd Wz=Ws, Wzp=Ws, Wz_old=Ws, delta_Wzp=Ws, gWs=Ws;
 	VectorXd Cz=Cs, Czp=Cs, Cz_old=Cs, delta_Czp=Cs, gCs=Cs;
 
@@ -99,6 +85,10 @@ malsar_result_t malsar_joint_feature_learning(
 		// add regularizer
 		Fs += Ws.squaredNorm();
 
+		//cout << "gWs" << endl << gWs << endl;
+		//cout << "gCs" << endl << gCs << endl;
+		//SG_SPRINT("Fs = %f\n",Fs);
+
 		double Fzp = 0.0;
 
 		int inner_iter = 0;
@@ -123,13 +113,13 @@ malsar_result_t malsar_joint_feature_learning(
 				int n_task_vecs = task_idx.vlen;
 				for (int i=0; i<n_task_vecs; i++)
 				{
-					double aa = -y[task_idx[i]]*(features->dense_dot(task_idx[i], Wzp.col(task).data(), n_feats)+Cs[task]);
+					double aa = -y[task_idx[i]]*(features->dense_dot(task_idx[i], Wzp.col(task).data(), n_feats)+Czp[task]);
 					double bb = CMath::max(aa,0.0);
 
 					Fzp += (CMath::log(CMath::exp(-bb) + CMath::exp(aa-bb)) + bb)/n_task_vecs;
 				}
 			}
-			Fzp += Wzp.squaredNorm();
+			Fzp += rho2*Wzp.squaredNorm();
 
 			// compute delta between line search point and search point
 			delta_Wzp = Wzp - Ws;
@@ -149,6 +139,7 @@ malsar_result_t malsar_joint_feature_learning(
 			// break if delta is getting too small
 			if (r_sum <= 1e-20)
 			{
+				SG_SDEBUG("Line search point is too close to search point\n");
 				done = true;
 				break;
 			}
@@ -170,8 +161,10 @@ malsar_result_t malsar_joint_feature_learning(
 		// compute objective value
 		obj_old = obj;
 		obj = Fzp;
-		for (task=0; task<n_tasks; task++)
-			obj += rho1*(Wz.col(task).norm());
+		for (int i=0; i<n_feats; i++)
+			obj += rho1*(Wz.row(i).lpNorm<2>());
+		//for (task=0; task<n_tasks; task++)
+		//	obj += rho1*(Wz.col(task).norm());
 		SG_SDEBUG("Obj = %f\n",obj);
 
 		// check if process should be terminated 
@@ -181,7 +174,10 @@ malsar_result_t malsar_joint_feature_learning(
 				if (iter>=2)
 				{
 					if ( CMath::abs(obj-obj_old) <= options.tolerance )
+					{
+						SG_SDEBUG("Objective changes less than tolerance\n");
 						done = true;
+					}
 				}
 			break;
 			case 1: