libshogun simple kNN example with random data

examples/undocumented/libshogun/Makefile

@@ -27,6 +27,7 @@ TARGETS = basic_minimal \
 		  classifier_qda \
 		  classifier_lda \
 		  classifier_multiclasslinearmachine \
+		  classifier_knn \
 		  kernel_gaussian kernel_revlin kernel_custom\
 		  library_dyn_int library_gc_array library_indirect_object \
 		  library_hash parameter_set_from_parameters \

examples/undocumented/libshogun/classifier_knn.cpp

@@ -0,0 +1,59 @@
+/*
+ * 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) 2013 Fernando J. Iglesias García
+ */
+
+#include <shogun/distance/EuclideanDistance.h>
+#include <shogun/features/DataGenerator.h>
+#include <shogun/features/DenseFeatures.h>
+#include <shogun/labels/MulticlassLabels.h>
+#include <shogun/multiclass/KNN.h>
+
+using namespace shogun;
+
+#define NUM  10
+#define DIMS 2
+#define CLASSES 4
+#define k 3
+
+int main(int, char*[])
+{
+	init_shogun_with_defaults();
+
+#ifdef HAVE_LAPACK /* because of CDataGenerator::generate_gaussians */
+
+	// Labels and features containers
+	SGVector<float64_t> lab(CLASSES*NUM);
+	SGMatrix<float64_t> feat(DIMS, CLASSES*NUM);
+	// Random generation of features
+	feat = CDataGenerator::generate_gaussians(NUM,CLASSES,DIMS);
+	// Labels
+	for (int32_t i = 0; i < CLASSES; ++i)
+		for (int32_t j = 0; j < NUM; ++j)
+			lab[i*NUM + j] = i;
+
+	// Create train labels
+	CMulticlassLabels* labels = new CMulticlassLabels(lab);
+	// Create train features
+	CDenseFeatures<float64_t>* features = new CDenseFeatures<float64_t>(feat);
+
+	// Create KNN classifier
+	CKNN* knn = new CKNN(k, new CEuclideanDistance(features, features), labels);
+	// Train classifier
+	knn->train();
+	// Apply classifier
+	CMulticlassLabels* output = CLabelsFactory::to_multiclass( knn->apply() );
+
+	// Free memory
+	SG_UNREF(knn)
+	SG_UNREF(output)
+
+#endif /* HAVE_LAPACK */
+
+	exit_shogun();
+	return 0;
+}

src/shogun/multiclass/KNN.cpp

@@ -123,10 +123,10 @@ SGMatrix<int32_t> CKNN::nearest_neighbors()
 	{
 		SG_PROGRESS(i, 0, n)
 
-		//lhs idx 0..n-1 (i.e., all train examples) and rhs idx i
+		//lhs idx 0..num train examples-1 (i.e., all train examples) and rhs idx i
 		distances_lhs(dists,0,m_train_labels.vlen-1,i);
 
-		//fill in an array with 0, 1,2, ..., num train examples
+		//fill in an array with 0..num train examples-1
 		for (int32_t j=0; j<m_train_labels.vlen; j++)
 			train_idxs[j]=j;