split.h File Reference

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Classes
struct	Operator< NT, S, Fit, enable_if_t< is_in_v< NT, NodeType::SplitOn, NodeType::SplitBest > > >

Namespaces
namespace	Split

Functions
template<typename T>
ArrayXb	Split::threshold_mask (const T &x, const float &threshold)
	Applies a learned threshold to a feature, returning a mask.
template<typename T> requires same_as<typename T::Scalar, bool>
ArrayXb	Split::threshold_mask (const T &x, const float &threshold)
	Applies a learned threshold to a feature, returning a mask.
template<typename T> requires same_as<typename T::Scalar, bJet>
ArrayXb	Split::threshold_mask (const T &x, const float &threshold)
	Applies a learned threshold to a feature, returning a mask.
template<typename T> requires same_as<typename T::Scalar, float>
ArrayXb	Split::threshold_mask (const T &x, const float &threshold)
	Applies a learned threshold to a feature, returning a mask.
template<typename T> requires same_as<typename T::Scalar, fJet>
ArrayXb	Split::threshold_mask (const T &x, const float &threshold)
	Applies a learned threshold to a feature, returning a mask.
template<typename T> requires same_as<typename T::Scalar, int>
ArrayXb	Split::threshold_mask (const T &x, const float &threshold)
	Applies a learned threshold to a feature, returning a mask.
template<typename T> requires same_as<typename T::Scalar, iJet>
ArrayXb	Split::threshold_mask (const T &x, const float &threshold)
	Applies a learned threshold to a feature, returning a mask.
float	Split::gini_impurity_index (const ArrayXf &classes, const vector< float > &uc)
float	Split::gain (const ArrayXf &lsplit, const ArrayXf &rsplit, bool classification, vector< float > unique_classes)
template<typename T>
vector< float >	Split::get_thresholds (const T &x)
tuple< string, float >	Split::get_best_variable_and_threshold (const Dataset &d, TreeNode &tn)
template<typename T>
tuple< float, float >	Split::best_threshold (const T &x, const ArrayXf &y, bool classification)
template<typename T>
void	Split::get_best_threshold_by_type (const Dataset &d, auto &results)
template<typename Ts, std::size_t... Is>
auto	Split::get_best_thresholds (const Dataset &d, std::index_sequence< Is... >)
template<typename T>
T	Split::stitch (array< T, 2 > &child_outputs, const ArrayXb &mask)
	Stitches together outputs from left or right child based on threshold.