OpenMS  2.6.0
SimpleSVM.h
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31 // $Maintainer: Hendrik Weisser $
32 // $Authors: Hendrik Weisser $
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34 
35 #pragma once
36 
38 
39 #include <svm.h>
40 
41 #include <map>
42 #include <vector>
43 #include <utility> // for "pair"
44 
45 namespace OpenMS
46 {
65  class OPENMS_DLLAPI SimpleSVM :
66  public DefaultParamHandler
67  {
68 
69  public:
71  typedef std::map<String, std::vector<double> > PredictorMap;
72 
74  typedef std::map<String, std::pair<double, double> > ScaleMap;
75 
77  struct Prediction
78  {
81 
83  std::map<Int, double> probabilities;
84  };
85 
87  SimpleSVM();
88 
90  ~SimpleSVM() override;
91 
102  void setup(PredictorMap& predictors, const std::map<Size, Int>& labels);
103 
113  void predict(std::vector<Prediction>& predictions,
114  std::vector<Size> indexes = std::vector<Size>()) const;
115 
124  void getFeatureWeights(std::map<String, double>& feature_weights) const;
125 
127  void writeXvalResults(const String& path) const;
128 
130  const ScaleMap& getScaling() const;
131  protected:
133  typedef std::vector<std::vector<double> > SVMPerformance;
134 
136  std::vector<std::vector<struct svm_node> > nodes_;
137 
139  struct svm_problem data_;
140 
142  struct svm_parameter svm_params_;
143 
145  struct svm_model* model_;
146 
148  std::vector<String> predictor_names_;
149 
152 
154  std::vector<double> log2_C_, log2_gamma_;
155 
158 
161 
163  static void printNull_(const char*) {}
164 
166  void scaleData_(PredictorMap& predictors);
167 
169  void convertData_(const PredictorMap& predictors);
170 
172  std::pair<double, double> chooseBestParameters_() const;
173 
175  void optimizeParameters_();
176  };
177 }
178 
OpenMS::SimpleSVM::SVMPerformance
std::vector< std::vector< double > > SVMPerformance
Classification performance for different param. combinations (C/gamma):
Definition: SimpleSVM.h:133
DefaultParamHandler.h
OpenMS::SimpleSVM::scaling_
ScaleMap scaling_
Mapping from predictor name to predictor min and max.
Definition: SimpleSVM.h:157
OpenMS::SimpleSVM::performance_
SVMPerformance performance_
Cross-validation results.
Definition: SimpleSVM.h:160
OpenMS::SimpleSVM
Simple interface to support vector machines for classification (via LIBSVM).
Definition: SimpleSVM.h:65
OpenMS::String
A more convenient string class.
Definition: String.h:59
OpenMS::Size
size_t Size
Size type e.g. used as variable which can hold result of size()
Definition: Types.h:127
OpenMS::SimpleSVM::ScaleMap
std::map< String, std::pair< double, double > > ScaleMap
Mapping from predictor name to predictor min and max.
Definition: SimpleSVM.h:74
OpenMS::SimpleSVM::Prediction::label
Int label
Predicted class label.
Definition: SimpleSVM.h:80
OpenMS::DefaultParamHandler
A base class for all classes handling default parameters.
Definition: DefaultParamHandler.h:92
OpenMS::SimpleSVM::log2_gamma_
std::vector< double > log2_gamma_
Definition: SimpleSVM.h:154
OpenMS
Main OpenMS namespace.
Definition: FeatureDeconvolution.h:46
OpenMS::SimpleSVM::n_parts_
Size n_parts_
Number of partitions for cross-validation.
Definition: SimpleSVM.h:151
OpenMS::SimpleSVM::nodes_
std::vector< std::vector< struct svm_node > > nodes_
Values of predictors (LIBSVM format)
Definition: SimpleSVM.h:136
OpenMS::SimpleSVM::Prediction
SVM prediction result.
Definition: SimpleSVM.h:77
int
OpenMS::SimpleSVM::printNull_
static void printNull_(const char *)
Dummy function to suppress LIBSVM output.
Definition: SimpleSVM.h:163
OpenMS::SimpleSVM::model_
struct svm_model * model_
Pointer to SVM model (LIBSVM format)
Definition: SimpleSVM.h:145
OpenMS::SimpleSVM::PredictorMap
std::map< String, std::vector< double > > PredictorMap
Mapping from predictor name to vector of predictor values.
Definition: SimpleSVM.h:71
OpenMS::SimpleSVM::Prediction::probabilities
std::map< Int, double > probabilities
Predicted probabilities for different classes.
Definition: SimpleSVM.h:83
OpenMS::SimpleSVM::predictor_names_
std::vector< String > predictor_names_
Names of predictors in the model (excluding uninformative ones)
Definition: SimpleSVM.h:148