SHOGUN  6.1.3
GaussianProcessClassification.h
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1 /*
2  * Copyright (c) The Shogun Machine Learning Toolbox
3  * Written (w) 2014 Wu Lin
4  * Written (W) 2013 Roman Votyakov
5  * All rights reserved.
6  *
7  * Redistribution and use in source and binary forms, with or without
8  * modification, are permitted provided that the following conditions are met:
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12  * 2. Redistributions in binary form must reproduce the above copyright notice,
13  * this list of conditions and the following disclaimer in the documentation
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16  * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
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30  *
31  * Code adapted from
32  * Gaussian Process Machine Learning Toolbox
33  * http://www.gaussianprocess.org/gpml/code/matlab/doc/
34  * and
35  * https://gist.github.com/yorkerlin/8a36e8f9b298aa0246a4
36  */
37 
38 #ifndef _GAUSSIANPROCESSCLASSIFICATION_H_
39 #define _GAUSSIANPROCESSCLASSIFICATION_H_
40 
41 
42 #include <shogun/lib/config.h>
44 #include <shogun/machine/Machine.h>
45 
46 namespace shogun
47 {
48 
53 {
54 public:
57 
60 
66 
68 
75  virtual CBinaryLabels* apply_binary(CFeatures* data=NULL);
76 
84 
92 
100 
106  {
108  }
109 
114  virtual const char* get_name() const
115  {
116  return "GaussianProcessClassification";
117  }
124  virtual CMulticlassLabels* apply_multiclass(CFeatures* data=NULL);
125 
126 protected:
133  virtual bool train_machine(CFeatures* data=NULL);
134 
135 };
136 }
137 #endif /* _GAUSSIANPROCESSCLASSIFICATION_H_ */
EMachineType
Definition: Machine.h:36
SGVector< float64_t > get_variance_vector(CFeatures *data)
A base class for Gaussian Processes.
Class GaussianProcessClassification implements binary and multiclass classification based on Gaussian...
SGVector< float64_t > get_mean_vector(CFeatures *data)
Multiclass Labels for multi-class classification.
SGVector< float64_t > get_probabilities(CFeatures *data)
virtual CBinaryLabels * apply_binary(CFeatures *data=NULL)
virtual bool train_machine(CFeatures *data=NULL)
all of classes and functions are contained in the shogun namespace
Definition: class_list.h:18
The Inference Method base class.
Definition: Inference.h:81
The class Features is the base class of all feature objects.
Definition: Features.h:69
Binary Labels for binary classification.
Definition: BinaryLabels.h:37
virtual CMulticlassLabels * apply_multiclass(CFeatures *data=NULL)

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