| OpenMS 2.5.0

SimpleSVM.h
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30 // --------------------------------------------------------------------------
31 // $Maintainer: Hendrik Weisser $
32 // $Authors: Hendrik Weisser $
33 // --------------------------------------------------------------------------
34
35 #pragma once
36
37 #include <OpenMS/DATASTRUCTURES/DefaultParamHandler.h>
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 struct Prediction
75 {
77 Int label;
78
80 std::map<Int, double> probabilities;
81 };
82
84 SimpleSVM();
85
87 ~SimpleSVM() override;
88
99 void setup(PredictorMap& predictors, const std::map<Size, Int>& labels);
100
110 void predict(std::vector<Prediction>& predictions,
111 std::vector<Size> indexes = std::vector<Size>()) const;
112
121 void getFeatureWeights(std::map<String, double>& feature_weights) const;
122
124 void writeXvalResults(const String& path) const;
125
126 protected:
128 typedef std::vector<std::vector<double> > SVMPerformance;
129
131 std::vector<std::vector<struct svm_node> > nodes_;
132
134 struct svm_problem data_;
135
137 struct svm_parameter svm_params_;
138
140 struct svm_model* model_;
141
143 std::vector<String> predictor_names_;
144
146 Size n_parts_;
147
149 std::vector<double> log2_C_, log2_gamma_;
150
152 SVMPerformance performance_;
153
155 static void printNull_(const char*) {}
156
158 void scaleData_(PredictorMap& predictors) const;
159
161 void convertData_(const PredictorMap& predictors);
162
164 std::pair<double, double> chooseBestParameters_() const;
165
167 void optimizeParameters_();
168 };
169 }
170
OpenMS::SimpleSVM::performance_
SVMPerformance performance_
Cross-validation results.
Definition: SimpleSVM.h:152
OpenMS::String
A more convenient string class.
Definition: String.h:58
OpenMS::SimpleSVM::model_
struct svm_model * model_
Pointer to SVM model (LIBSVM format)
Definition: SimpleSVM.h:140
OpenMS::SimpleSVM::printNull_
static void printNull_(const char *)
Dummy function to suppress LIBSVM output.
Definition: SimpleSVM.h:155
OpenMS::SimpleSVM::predictor_names_
std::vector< String > predictor_names_
Names of predictors in the model (excluding uninformative ones)
Definition: SimpleSVM.h:143
OpenMS::DefaultParamHandler
A base class for all classes handling default parameters.
Definition: DefaultParamHandler.h:91
OpenMS::SimpleSVM::log2_gamma_
std::vector< double > log2_gamma_
Definition: SimpleSVM.h:149
OpenMS::SimpleSVM::Prediction::probabilities
std::map< Int, double > probabilities
Predicted probabilities for different classes.
Definition: SimpleSVM.h:80
OpenMS::SimpleSVM::Prediction::label
Int label
Predicted class label.
Definition: SimpleSVM.h:77
OpenMS::SimpleSVM::Prediction
SVM prediction result.
Definition: SimpleSVM.h:74
OpenMS::SimpleSVM::nodes_
std::vector< std::vector< struct svm_node > > nodes_
Values of predictors (LIBSVM format)
Definition: SimpleSVM.h:131
OpenMS::SimpleSVM::SVMPerformance
std::vector< std::vector< double > > SVMPerformance
Classification performance for different param. combinations (C/gamma):
Definition: SimpleSVM.h:128
OpenMS::SimpleSVM
Simple interface to support vector machines for classification (via LIBSVM).
Definition: SimpleSVM.h:65
OpenMS
Main OpenMS namespace.
Definition: FeatureDeconvolution.h:46
DefaultParamHandler.h
OpenMS::SimpleSVM::PredictorMap
std::map< String, std::vector< double > > PredictorMap
Mapping from predictor name to vector of predictor values.
Definition: SimpleSVM.h:71
int
OpenMS::SimpleSVM::n_parts_
Size n_parts_
Number of partitions for cross-validation.
Definition: SimpleSVM.h:146
OpenMS::Size
size_t Size
Size type e.g. used as variable which can hold result of size()
Definition: Types.h:127