forpy 2

Class Hierarchy
This inheritance list is sorted roughly, but not completely, alphabetically:
[detail level 1 2 3]

C forpy::DeciderDesk | Desk for decider training
C forpy::Desk | Main thread desk object
C forpy::Empty | A struct to represent an empty variant
▼C std::exception | STL class
▼C forpy::ForpyException |
C forpy::EmptyException |
▼C forpy::Forest |
C forpy::ClassificationForest |
C forpy::RegressionForest |
C forpy::get_core< T > | Get the core datatype with removed pointer, reference and const modifiers
▼C forpy::IDataProvider | A data provider for the training of one tree
C forpy::FastDProv | Use the provided data plain throughout the training
▼C forpy::IDecider | Interface for the decider. It does the optimization of the deciding classifier for each node and stores the parameters
C forpy::FastDecider | A classifier manager for weak classifiers with a filter function, a feature calculation function and a thresholding
▼C forpy::IEntropyFunction | Interface for an entropy calculation functor
C forpy::ClassificationError | Computes the classification error as \(1-\max(p_i)\)
C forpy::InducedEntropy | Computes the induced p entropy
C forpy::RenyiEntropy | Computes the Renyi entropy
C forpy::ShannonEntropy | Computes the classical Shannon-Entropy
C forpy::TsallisEntropy | Computes the Tsallis entropy
▼C forpy::IGainCalculator | Interface for a gain calculator class
C forpy::EntropyGain | Calculates the gain as difference of current entropy and the weighted sum of subgroup entropies
▼C forpy::ILeaf | Stores and returns leaf values, and combines them to forest results
C forpy::ClassificationLeaf | Stores the probability distributions for n_classes at a leaf
C forpy::RegressionLeaf | Manages the leaf nodes of regression trees
▼C forpy::IThreshOpt | Find an optimal threshold
▼C forpy::ClassificationOpt | Optimize split thresholds to optimize classification results
C forpy::FastClassOpt | Optimize split thresholds to optimize classification results
C forpy::RegressionOpt | Optimize split thresholds to optimize regression results (MSE)
C forpy::LeafDesk | Desk for leaf manager training
C forpy::MatEqVis | Comparison visitor
C forpy::Name< T > | Struct for translating primitive types to a short name
C forpy::Name< double > |
C forpy::Name< float > |
C forpy::Name< int > |
C forpy::Name< int16_t > |
C forpy::Name< uint > |
C forpy::Name< uint8_t > |
C forpy::threading::detail::Queue< T > |
C forpy::threading::detail::Queue< std::function< void(forpy::Desk)> *> |
C forpy::RandomDesk | Desk for coordinating the random engines
C forpy::SamplingWithoutReplacement< T > | A lazy evaluation sampling without replacement
C forpy::SplitOptRes< FT > |
C forpy::threading::thread_pool |
C forpy::ThreadControl |
C forpy::TodoMark | Stores the parameters for one marked tree node
▼C forpy::Tree | The main tree class for the forpy framework
C forpy::ClassificationTree |
C forpy::RegressionTree |
C forpy::TreeDesk | Desk for tree training
▼C variant |
C forpy::ptr_variant< Ts > |
C forpy::vector_hasher | A simple vector<size_t> hasher
C forpy::VReset | Call the reset operation on a pointer variant