Proper way to handle W in OCAS SVM

shogun-toolbox · Mar 22, 2017 · b7b9dfe · b7b9dfe
1 parent bf1b262
commit b7b9dfe
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Showing 2 changed files with 13 additions and 15 deletions.
diff --git a/src/shogun/classifier/svm/SVMOcas.cpp b/src/shogun/classifier/svm/SVMOcas.cpp
@@ -74,18 +74,18 @@ bool CSVMOcas::train_machine(CFeatures* data)
 	for (int32_t i=0; i<num_vec; i++)
 		lab[i] = ((CBinaryLabels*)m_labels)->get_label(i);
 
-	SGVector<float64_t> w(features->get_dim_feature_space());
-	w.zero();
+	current_w = SGVector<float64_t>(features->get_dim_feature_space());
+	current_w.zero();
 
 	if (num_vec!=lab.vlen || num_vec<=0)
 		SG_ERROR("num_vec=%d num_train_labels=%d\n", num_vec, lab.vlen)
 
 	SG_FREE(old_w);
-	old_w=SG_CALLOC(float64_t, w.vlen);
+	old_w=SG_CALLOC(float64_t, current_w.vlen);
 	bias=0;
 	old_bias=0;
 
-	tmp_a_buf=SG_CALLOC(float64_t, w.vlen);
+	tmp_a_buf=SG_CALLOC(float64_t, current_w.vlen);
 	cp_value=SG_CALLOC(float64_t*, bufsize);
 	cp_index=SG_CALLOC(uint32_t*, bufsize);
 	cp_nz_dims=SG_CALLOC(uint32_t, bufsize);
@@ -144,7 +144,7 @@ bool CSVMOcas::train_machine(CFeatures* data)
 	SG_FREE(old_w);
 	old_w=NULL;
 
-	set_w(w);
+	set_w(current_w);
 
 	return true;
 }
@@ -160,9 +160,8 @@ float64_t CSVMOcas::update_W( float64_t t, void* ptr )
 {
   float64_t sq_norm_W = 0;
   CSVMOcas* o = (CSVMOcas*) ptr;
-  SGVector<float64_t> w = o->get_w();
-  uint32_t nDim = (uint32_t) w.vlen;
-  float64_t* W = w.vector;
+  uint32_t nDim = (uint32_t) o->current_w.vlen;
+  float64_t* W = o->current_w.vector;
   float64_t* oldW=o->old_w;
 
   for(uint32_t j=0; j <nDim; j++)
@@ -190,8 +189,7 @@ int CSVMOcas::add_new_cut(
 {
 	CSVMOcas* o = (CSVMOcas*) ptr;
 	CDotFeatures* f = o->features;
-	SGVector<float64_t> w = o->get_w();
-	uint32_t nDim=(uint32_t) w.vlen;
+	uint32_t nDim=(uint32_t) o->current_w.vlen;
 	float64_t* y = o->lab.vector;
 
 	float64_t** c_val = o->cp_value;
@@ -277,16 +275,14 @@ int CSVMOcas::compute_output(float64_t *output, void* ptr)
 	CSVMOcas* o = (CSVMOcas*) ptr;
 	CDotFeatures* f=o->features;
 	int32_t nData=f->get_num_vectors();
-	SGVector<float64_t> w = o->get_w();
+	SGVector<float64_t> w(o->get_w());
 
 	float64_t* y = o->lab.vector;
 
-	f->dense_dot_range(output, 0, nData, y, w.vector, w.vlen, 0.0);
+	f->dense_dot_range(output, 0, nData, y, o->current_w.vector, o->current_w.vlen, 0.0);
 
 	for (int32_t i=0; i<nData; i++)
 		output[i]+=y[i]*o->bias;
-	//CMath::display_vector(w, w.vlen, "w");
-	//CMath::display_vector(output, nData, "out");
 	return 0;
 }
 
@@ -304,7 +300,7 @@ void CSVMOcas::compute_W(
 	void* ptr )
 {
 	CSVMOcas* o = (CSVMOcas*) ptr;
-	SGVector<float64_t> w_vector = o->get_w();
+	SGVector<float64_t> w_vector(o->get_w());
 	uint32_t nDim= (uint32_t) w_vector.vlen;
 	CMath::swap(w_vector.vector, o->old_w);
 	float64_t* W=w_vector.vector;

diff --git a/src/shogun/classifier/svm/SVMOcas.h b/src/shogun/classifier/svm/SVMOcas.h
@@ -212,6 +212,8 @@ class CSVMOcas : public CLinearMachine
 		/** method */
 		E_SVM_TYPE method;
 
+		/** current W */
+		SGVector<float64_t> current_w;
 		/** old W */
 		float64_t* old_w;
 		/** old bias */