Made GaussianNaiveBayes a multiclass machine

- Added NativeMulticlassMachine for classifiers without submachines
shogun-toolbox · May 21, 2012 · 54eef53 · 54eef53
1 parent d91047e
commit 54eef53
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Showing 5 changed files with 98 additions and 18 deletions.
diff --git a/src/interfaces/modular/Multiclass.i b/src/interfaces/modular/Multiclass.i
@@ -16,6 +16,7 @@
 %rename(MulticlassOneVsRestStrategy) CMulticlassOneVsRestStrategy;
 %rename(MulticlassOneVsOneStrategy) CMulticlassOneVsOneStrategy;
 %rename(MulticlassMachine) CMulticlassMachine;
+%rename(NativeMulticlassMachine) CNativeMulticlassMachine;
 %rename(LinearMulticlassMachine) CLinearMulticlassMachine;
 %rename(KernelMulticlassMachine) CKernelMulticlassMachine;
 %rename(MulticlassSVM) CMulticlassSVM;
@@ -53,6 +54,7 @@
 %include <shogun/multiclass/MulticlassOneVsRestStrategy.h>
 %include <shogun/multiclass/MulticlassOneVsOneStrategy.h>
 %include <shogun/machine/MulticlassMachine.h>
+%include <shogun/machine/NativeMulticlassMachine.h>
 %include <shogun/machine/LinearMulticlassMachine.h>
 %include <shogun/machine/KernelMulticlassMachine.h>
 %include <shogun/multiclass/MulticlassSVM.h>

diff --git a/src/interfaces/modular/Multiclass_includes.i b/src/interfaces/modular/Multiclass_includes.i
@@ -4,6 +4,7 @@
  #include <shogun/multiclass/MulticlassOneVsRestStrategy.h>
  #include <shogun/multiclass/MulticlassOneVsOneStrategy.h>
  #include <shogun/machine/MulticlassMachine.h>
+ #include <shogun/machine/NativeMulticlassMachine.h>
  #include <shogun/machine/LinearMulticlassMachine.h>
  #include <shogun/machine/KernelMulticlassMachine.h>
  #include <shogun/multiclass/MulticlassSVM.h>

diff --git a/src/shogun/machine/NativeMulticlassMachine.h b/src/shogun/machine/NativeMulticlassMachine.h
@@ -0,0 +1,76 @@
+/*
+ * 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) 1999-2011 Soeren Sonnenburg
+ * Written (W) 2012 Fernando José Iglesias García and Sergey Lisitsyn
+ * Copyright (C) 2012 Sergey Lisitsyn, Fernando José Iglesias Garcia
+ */
+
+#ifndef _NATIVEMULTICLASSMACHINE_H___
+#define _NATIVEMULTICLASSMACHINE_H___
+
+#include <shogun/machine/MulticlassMachine.h>
+
+namespace shogun
+{
+
+/** @brief experimental abstract native multiclass machine class */
+class CNativeMulticlassMachine : public CMulticlassMachine
+{
+	public:
+		/** default constructor  */
+		CNativeMulticlassMachine()
+		{
+		}
+
+		/** destructor */
+		virtual ~CNativeMulticlassMachine()
+		{
+		}
+
+		/** get name */
+		virtual const char* get_name() const
+		{
+			return "NativeMulticlassMachine";
+		}
+
+	protected:
+		/** init strategy */
+		void init_strategy() { }
+
+		/** clear machines */
+		void clear_machines() { }
+
+		/** abstract init machine for training method */
+		virtual bool init_machine_for_train(CFeatures* data) { return true; }
+
+		/** abstract init machines for applying method */
+		virtual bool init_machines_for_apply(CFeatures* data) { return true; }
+
+		/** check whether machine is ready */
+		virtual bool is_ready() { return true; }
+
+		/** obtain machine from trained one */
+		virtual CMachine* get_machine_from_trained(CMachine* machine) { return NULL; }
+
+		/** get num rhs vectors */
+		virtual int32_t get_num_rhs_vectors() { return 0; }
+
+		/** set subset to the features of the machine, deletes old one
+		 *
+		 * @param subset subset indices to set
+		 */
+		virtual void add_machine_subset(SGVector<index_t> subset) { }
+
+		/** deletes any subset set to the features of the machine */
+		virtual void remove_machine_subset() { }
+
+		/** whether the machine is acceptable in set_machine */
+		virtual bool is_acceptable_machine(CMachine *machine) { return true; }
+
+};
+}
+#endif
diff --git a/src/shogun/multiclass/GaussianNaiveBayes.cpp b/src/shogun/multiclass/GaussianNaiveBayes.cpp
@@ -9,7 +9,6 @@
  */
 
 #include <shogun/multiclass/GaussianNaiveBayes.h>
-#include <shogun/machine/Machine.h>
 #include <shogun/features/Features.h>
 #include <shogun/labels/Labels.h>
 #include <shogun/labels/RegressionLabels.h>
@@ -19,15 +18,15 @@
 
 using namespace shogun;
 
-CGaussianNaiveBayes::CGaussianNaiveBayes() : CMachine(), m_features(NULL),
+CGaussianNaiveBayes::CGaussianNaiveBayes() : CNativeMulticlassMachine(), m_features(NULL),
 	m_min_label(0), m_num_classes(0), m_dim(0), m_means(), m_variances(),
 	m_label_prob(), m_rates()
 {
 
 };
 
 CGaussianNaiveBayes::CGaussianNaiveBayes(CFeatures* train_examples,
-	CLabels* train_labels) : CMachine(), m_features(NULL),
+	CLabels* train_labels) : CNativeMulticlassMachine(), m_features(NULL),
 	m_min_label(0), m_num_classes(0), m_dim(0), m_means(),
 	m_variances(), m_label_prob(), m_rates()
 {
@@ -61,7 +60,7 @@ void CGaussianNaiveBayes::set_features(CFeatures* features)
 	m_features = (CDotFeatures*)features;
 }
 
-bool CGaussianNaiveBayes::train(CFeatures* data)
+bool CGaussianNaiveBayes::train_machine(CFeatures* data)
 {
 	// init features with data if necessary and assure type is correct
 	if (data)
@@ -173,7 +172,7 @@ bool CGaussianNaiveBayes::train(CFeatures* data)
 	return true;
 }
 
-CLabels* CGaussianNaiveBayes::apply(CFeatures* data)
+CMulticlassLabels* CGaussianNaiveBayes::apply_multiclass(CFeatures* data)
 {
 	if (data)
 		set_features(data);
@@ -184,20 +183,20 @@ CLabels* CGaussianNaiveBayes::apply(CFeatures* data)
 	int32_t num_vectors = m_features->get_num_vectors();
 
 	// init result labels
-	CRegressionLabels* result = new CRegressionLabels(num_vectors);
+	CMulticlassLabels* result = new CMulticlassLabels(num_vectors);
 
 	// classify each example of data
 	SG_PROGRESS(0, 0, num_vectors);
 	for (int i = 0; i < num_vectors; i++)
 	{
-		result->set_label(i,apply(i));
+		result->set_label(i,apply_one(i));
 		SG_PROGRESS(i + 1, 0, num_vectors);
 	}
 	SG_DONE();
 	return result;
 };
 
-float64_t CGaussianNaiveBayes::apply(int32_t idx)
+float64_t CGaussianNaiveBayes::apply_one(int32_t idx)
 {
 	// get [idx] feature vector
 	SGVector<float64_t> feature_vector = m_features->get_computed_dot_feature_vector(idx);

diff --git a/src/shogun/multiclass/GaussianNaiveBayes.h b/src/shogun/multiclass/GaussianNaiveBayes.h
@@ -11,7 +11,7 @@
 #ifndef GAUSSIANNAIVEBAYES_H_
 #define GAUSSIANNAIVEBAYES_H_
 
-#include <shogun/machine/Machine.h>
+#include <shogun/machine/NativeMulticlassMachine.h>
 #include <shogun/mathematics/Math.h>
 #include <shogun/features/DotFeatures.h>
 
@@ -32,7 +32,7 @@ class CFeatures;
  * \f]
  *
  */
-class CGaussianNaiveBayes : public CMachine
+class CGaussianNaiveBayes : public CNativeMulticlassMachine
 {
 
 public:
@@ -62,23 +62,17 @@ class CGaussianNaiveBayes : public CMachine
 	 */
 	virtual CFeatures* get_features();
 
-	/** train classifier
-	 * @param data train examples
-	 * @return true if successful
-	 */
-	virtual bool train(CFeatures* data=NULL);
-
 	/** classify specified examples
 	 * @param data examples to be classified
 	 * @return labels corresponding to data
 	 */
-	virtual CLabels* apply(CFeatures* data=NULL);
+	virtual CMulticlassLabels* apply_multiclass(CFeatures* data=NULL);
 
 	/** classifiy specified example
 	 * @param idx example index
 	 * @return label
 	 */
-	virtual float64_t apply(int32_t idx);
+	virtual float64_t apply_one(int32_t idx);
 
 	/** get name
 	 * @return classifier name
@@ -92,6 +86,14 @@ class CGaussianNaiveBayes : public CMachine
 
 protected:
 
+	/** train classifier
+	 * @param data train examples
+	 * @return true if successful
+	 */
+	virtual bool train_machine(CFeatures* data=NULL);
+
+protected: 
+
 	/// features for training or classifying
 	CDotFeatures* m_features;