12 #ifndef MLPACK_METHODS_ADABOOST_ADABOOST_MODEL_HPP 13 #define MLPACK_METHODS_ADABOOST_ADABOOST_MODEL_HPP 39 size_t weakLearnerType;
45 size_t dimensionality;
53 const size_t weakLearnerType);
68 const arma::Col
& Mappings() const { return mappings; } 83 void Train(
const arma::mat& data,
84 const arma::Row
& labels, 85 const size_t numClasses,
86 const size_t iterations,
87 const double tolerance);
90 void Classify(
const arma::mat& testData,
91 arma::Row
& predictions); 94 void Classify(
const arma::mat& testData,
95 arma::Row
& predictions, 96 arma::mat& probabilities);
99 template<
typename Archive>
102 if (Archive::is_loading::value)
113 ar & BOOST_SERIALIZATION_NVP(mappings);
114 ar & BOOST_SERIALIZATION_NVP(weakLearnerType);
115 if (weakLearnerType == WeakLearnerTypes::DECISION_STUMP)
116 ar & BOOST_SERIALIZATION_NVP(dsBoost);
117 else if (weakLearnerType == WeakLearnerTypes::PERCEPTRON)
118 ar & BOOST_SERIALIZATION_NVP(pBoost);
119 ar & BOOST_SERIALIZATION_NVP(dimensionality);
~AdaBoostModel()
Clean up memory.
void Classify(const arma::mat &testData, arma::Row< size_t > &predictions)
Classify test points.
Linear algebra utility functions, generally performed on matrices or vectors.
size_t & Dimensionality()
Modify the dimensionality of the model.
void serialize(Archive &ar, const unsigned int)
Serialize the model.
The model to save to disk.
arma::Col< size_t > & Mappings()
Modify the mappings.
void Train(const arma::mat &data, const arma::Row< size_t > &labels, const size_t numClasses, const size_t iterations, const double tolerance)
Train the model, treat the data is all of the numeric type.
Include all of the base components required to write mlpack methods, and the main mlpack Doxygen docu...
size_t WeakLearnerType() const
Get the weak learner type.
AdaBoostModel()
Create an empty AdaBoost model.
const arma::Col< size_t > & Mappings() const
Get the mappings.
AdaBoostModel & operator=(const AdaBoostModel &other)
Copy assignment operator.
size_t Dimensionality() const
Get the dimensionality of the model.
size_t & WeakLearnerType()
Modify the weak learner type.