mlpack
mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType > Member List

This is the complete list of members for mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >, including all inherited members.

CalculateDirection(const VecType &point) constmlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
CategoricalSplit typedefmlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
CheckInterval() constmlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >inline
CheckInterval(const size_t checkInterval)mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
Child(const size_t i) constmlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >inline
Child(const size_t i)mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >inline
Classify(const VecType &point) constmlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
Classify(const VecType &point, size_t &prediction, double &probability) constmlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
Classify(const MatType &data, arma::Row< size_t > &predictions) constmlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
Classify(const MatType &data, arma::Row< size_t > &predictions, arma::rowvec &probabilities) constmlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
CreateChildren()mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
HoeffdingTree(const MatType &data, const data::DatasetInfo &datasetInfo, const arma::Row< size_t > &labels, const size_t numClasses, const bool batchTraining=true, const double successProbability=0.95, const size_t maxSamples=0, const size_t checkInterval=100, const size_t minSamples=100, const CategoricalSplitType< FitnessFunction > &categoricalSplitIn=CategoricalSplitType< FitnessFunction >(0, 0), const NumericSplitType< FitnessFunction > &numericSplitIn=NumericSplitType< FitnessFunction >(0))mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
HoeffdingTree(const data::DatasetInfo &datasetInfo, const size_t numClasses, const double successProbability=0.95, const size_t maxSamples=0, const size_t checkInterval=100, const size_t minSamples=100, const CategoricalSplitType< FitnessFunction > &categoricalSplitIn=CategoricalSplitType< FitnessFunction >(0, 0), const NumericSplitType< FitnessFunction > &numericSplitIn=NumericSplitType< FitnessFunction >(0), std::unordered_map< size_t, std::pair< size_t, size_t >> *dimensionMappings=NULL, const bool copyDatasetInfo=true)mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
HoeffdingTree()mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
HoeffdingTree(const HoeffdingTree &other)mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
HoeffdingTree(HoeffdingTree &&other)mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
MajorityClass() constmlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >inline
MajorityClass()mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >inline
MajorityProbability() constmlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >inline
MajorityProbability()mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >inline
MaxSamples() constmlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >inline
MaxSamples(const size_t maxSamples)mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
MinSamples() constmlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >inline
MinSamples(const size_t minSamples)mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
NumChildren() constmlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >inline
NumDescendants() constmlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
NumericSplit typedefmlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
operator=(const HoeffdingTree &other)mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
operator=(HoeffdingTree &&other)mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
serialize(Archive &ar, const uint32_t)mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
SplitCheck()mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
SplitDimension() constmlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >inline
SuccessProbability() constmlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >inline
SuccessProbability(const double successProbability)mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
Train(const MatType &data, const arma::Row< size_t > &labels, const bool batchTraining=true, const bool resetTree=false, const size_t numClasses=0)mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
Train(const MatType &data, const data::DatasetInfo &info, const arma::Row< size_t > &labels, const bool batchTraining=true, const size_t numClasses=0)mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
Train(const VecType &point, const size_t label)mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >
~HoeffdingTree()mlpack::tree::HoeffdingTree< FitnessFunction, NumericSplitType, CategoricalSplitType >