OpenMS  3.0.0
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 #include <tuple>
45 
46 namespace OpenMS
47 {
66  class OPENMS_DLLAPI SimpleSVM :
67  public DefaultParamHandler
68  {
69 
70  public:
72  typedef std::map<String, std::vector<double> > PredictorMap;
73 
75  typedef std::map<String, std::pair<double, double> > ScaleMap;
76 
78  struct Prediction
79  {
81  double label;
82 
84  std::map<double, double> probabilities;
85  };
86 
88  SimpleSVM();
89 
91  ~SimpleSVM() override;
92 
104  void setup(PredictorMap& predictors, const std::map<Size, double>& labels, bool classification = true);
105 
115  void predict(std::vector<Prediction>& predictions,
116  std::vector<Size> indexes = std::vector<Size>()) const;
117 
118  void predict(PredictorMap& predictors, std::vector<Prediction>& predictions) const;
119 
128  void getFeatureWeights(std::map<String, double>& feature_weights) const;
129 
131  void writeXvalResults(const String& path) const;
132 
134  const ScaleMap& getScaling() const;
135  protected:
136 
137  void clear_();
138 
140  typedef std::vector<std::vector<std::vector<double>>> SVMPerformance;
141 
143  std::vector<std::vector<struct svm_node> > nodes_;
144 
146  struct svm_problem data_;
147 
149  struct svm_parameter svm_params_;
150 
152  struct svm_model* model_;
153 
155  std::vector<String> predictor_names_;
156 
159 
161  std::vector<double> log2_C_, log2_gamma_, log2_p_;
162 
165 
168 
170  static void printNull_(const char*) {}
171 
173  void scaleData_(PredictorMap& predictors);
174 
176  void convertData_(const PredictorMap& predictors);
177 
179  std::tuple<double, double, double> chooseBestParameters_(bool higher_better) const;
180 
182  void optimizeParameters_(bool classification);
183  };
184 }
185 
SVMPerformance performance_
Cross-validation results.
Definition: SimpleSVM.h:167
A more convenient string class.
Definition: String.h:58
std::vector< std::vector< std::vector< double > > > SVMPerformance
Classification performance for different param. combinations (C/gamma/p):
Definition: SimpleSVM.h:140
std::map< String, std::pair< double, double > > ScaleMap
Mapping from predictor name to predictor min and max.
Definition: SimpleSVM.h:75
std::vector< String > predictor_names_
Names of predictors in the model (excluding uninformative ones)
Definition: SimpleSVM.h:155
SVM prediction result.
Definition: SimpleSVM.h:78
struct svm_model * model_
Pointer to SVM model (LIBSVM format)
Definition: SimpleSVM.h:152
Main OpenMS namespace.
Definition: FeatureDeconvolution.h:47
std::vector< std::vector< struct svm_node > > nodes_
Values of predictors (LIBSVM format)
Definition: SimpleSVM.h:143
ScaleMap scaling_
Mapping from predictor name to predictor min and max.
Definition: SimpleSVM.h:164
std::vector< double > log2_p_
Definition: SimpleSVM.h:161
static void printNull_(const char *)
Dummy function to suppress LIBSVM output.
Definition: SimpleSVM.h:170
std::map< double, double > probabilities
Class label and their predicted probabilities.
Definition: SimpleSVM.h:84
Simple interface to support vector machines for classification and regression (via LIBSVM)...
Definition: SimpleSVM.h:66
Size n_parts_
Number of partitions for cross-validation.
Definition: SimpleSVM.h:158
double label
Predicted class label or regression value.
Definition: SimpleSVM.h:81
size_t Size
Size type e.g. used as variable which can hold result of size()
Definition: Types.h:127
A base class for all classes handling default parameters.
Definition: DefaultParamHandler.h:92
std::map< String, std::vector< double > > PredictorMap
Mapping from predictor name to vector of predictor values.
Definition: SimpleSVM.h:72