Merge pull request #595 from uricamic/BM_SOL_EXAMPLE

BMRM SOL Multiclass example
shogun-toolbox · Jun 21, 2012 · 9c2be58 · 9c2be58
2 parents a53beb2 + a5c9046
commit 9c2be58
Showing 1 changed file with 155 additions and 0 deletions.
diff --git a/examples/undocumented/libshogun/so_multiclass_BMRM.cpp b/examples/undocumented/libshogun/so_multiclass_BMRM.cpp
@@ -0,0 +1,155 @@
+/*
+ * This program is free software; you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation; either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * Written (W) 2012 Michal Uricar
+ * Copyright (C) 2012 Michal Uricar
+ */
+
+#include <shogun/classifier/svm/LibLinear.h>
+#include <shogun/features/DenseFeatures.h>
+#include <shogun/io/SGIO.h>
+#include <shogun/labels/MulticlassLabels.h>
+#include <shogun/labels/StructuredLabels.h>
+#include <shogun/lib/common.h>
+#include <shogun/loss/HingeLoss.h>
+#include <shogun/machine/LinearMulticlassMachine.h>
+#include <shogun/mathematics/Math.h>
+#include <shogun/multiclass/MulticlassOneVsRestStrategy.h>
+#include <shogun/structure/MulticlassSOLabels.h>
+#include <shogun/structure/MulticlassModel.h>
+#include <shogun/structure/DualLibQPBMSOSVM.h>
+#include <shogun/structure/MulticlassRiskFunction.h>
+
+using namespace shogun;
+
+#define	DIMS		2
+#define EPSILON  	0
+#define	NUM_SAMPLES	10
+#define NUM_CLASSES	3
+
+char FNAME[] = "data.out";
+
+void gen_rand_data(SGVector< float64_t > labs, SGMatrix< float64_t > feats)
+{
+	float64_t means[DIMS];
+	float64_t  stds[DIMS];
+
+	FILE* pfile = fopen(FNAME, "w");
+
+	for ( int32_t c = 0 ; c < NUM_CLASSES ; ++c )
+	{
+		for ( int32_t j = 0 ; j < DIMS ; ++j )
+		{
+			means[j] = CMath::random(-1000, 1000);
+			stds[j] = CMath::random(   1,   5);
+		}
+
+		for ( int32_t i = 0 ; i < NUM_SAMPLES ; ++i )
+		{
+			labs[c*NUM_SAMPLES+i] = c;
+
+			fprintf(pfile, "%d", c);
+
+			for ( int32_t j = 0 ; j < DIMS ; ++j )
+			{
+				feats[(c*NUM_SAMPLES+i)*DIMS + j] =
+					CMath::normal_random(means[j], stds[j]);
+
+				fprintf(pfile, " %f", feats[(c*NUM_SAMPLES+i)*DIMS + j]);
+			}
+
+			fprintf(pfile, "\n");
+		}
+	}
+}
+
+int main(int argc, char * argv[])
+{
+	init_shogun_with_defaults();
+
+	SGVector< float64_t > labs(NUM_CLASSES*NUM_SAMPLES);
+	SGMatrix< float64_t > feats(DIMS, NUM_CLASSES*NUM_SAMPLES);
+
+	gen_rand_data(labs, feats);
+
+	// Create train labels
+	CMulticlassSOLabels* labels = new CMulticlassSOLabels(labs);
+	CMulticlassLabels*  mlabels = new CMulticlassLabels(labs);
+
+	// Create train features
+	CDenseFeatures< float64_t >* features = new CDenseFeatures< float64_t >(feats);
+
+	// Create structured model
+	CMulticlassModel* model = new CMulticlassModel(features, labels);
+
+	// Create loss function
+	CHingeLoss* loss = new CHingeLoss();
+
+	// Create risk function
+	CMulticlassRiskFunction* risk = new CMulticlassRiskFunction();
+
+	// Create SO-SVM
+	CDualLibQPBMSOSVM* sosvm = new CDualLibQPBMSOSVM(model, loss, labels, features, 0.01, risk);
+	SG_REF(sosvm);
+
+	sosvm->train();
+	CStructuredLabels* out = CStructuredLabels::obtain_from_generic(sosvm->apply());
+	SG_REF(out);
+
+	SG_SPRINT("\nJust after sosvm-train();\n\n");
+
+	// Create liblinear svm classifier with L2-regularized L2-loss
+	CLibLinear* svm = new CLibLinear(L2R_L2LOSS_SVC);
+
+	// Add some configuration to the svm
+	svm->set_epsilon(EPSILON);
+	svm->set_bias_enabled(false);
+
+	// Create a multiclass svm classifier that consists of several of the previous one
+	CLinearMulticlassMachine* mc_svm =
+		new CLinearMulticlassMachine( new CMulticlassOneVsRestStrategy(),
+				(CDotFeatures*) features, svm, mlabels);
+	SG_REF(mc_svm);
+
+	// Train the multiclass machine using the data passed in the constructor
+	mc_svm->train();
+	CMulticlassLabels* mout = CMulticlassLabels::obtain_from_generic(mc_svm->apply());
+	SG_REF(mout);
+
+	//SGVector< float64_t > slacks = sosvm->get_slacks();
+	for ( int i = 0 ; i < out->get_num_labels() ; ++i )
+	{
+		SG_SPRINT("%.0f %.0f %.0f\n",
+				mlabels->get_label(i),
+				( (CRealNumber*) out->get_label(i) )->value,
+				mout->get_label(i));
+	}
+
+	SG_SPRINT("\n");
+	SGVector< float64_t > w = sosvm->get_w();
+	for ( int32_t i = 0 ; i < w.vlen ; ++i )
+		SG_SPRINT("%10f ", w[i]);
+	SG_SPRINT("\n\n");
+
+	for ( int32_t i = 0 ; i < NUM_CLASSES ; ++i )
+	{
+		SGVector< float64_t > mw =
+			((CLinearMachine*) mc_svm->get_machine(i))->get_w();
+		for ( int32_t j = 0 ; j < mw.vlen ; ++j )
+			SG_SPRINT("%10f ", mw[j]);
+	}
+	SG_SPRINT("\n");
+
+	// Free memory
+	SG_UNREF(mout);
+	SG_UNREF(mc_svm);
+	SG_UNREF(sosvm);
+	SG_UNREF(out);
+
+	exit_shogun();
+
+	return 0;
+}