Stats.hpp File Reference

#include "utils/RangeVector.hpp"
#include "utils/Types.hpp"
#include <algorithm>
#include <cmath>
#include <map>
#include <set>
#include <stdexcept>
#include <vector>
#include <Eigen/Dense>
#include <pcg_random.hpp>

Go to the source code of this file.

Namespaces
namespace	ppforest2
	Binarization strategies for multiclass-to-binary reduction.
namespace	ppforest2::stats
	Statistical infrastructure for training and evaluation.

Typedefs
using	ppforest2::stats::RNG = pcg32

Functions
std::map< types::GroupId, int >	ppforest2::stats::group_indices (std::set< types::GroupId > const &groups)
	Map each label in groups to its index in iteration order.
types::Outcome	ppforest2::stats::majority_vote (std::vector< types::Outcome > const &preds)
	Majority vote over a sequence of integer-coded class labels.
types::Outcome	ppforest2::stats::mean (std::vector< types::Outcome > const &preds)
	Arithmetic mean of a sequence of outcome values.
template<typename Derived>
double	ppforest2::stats::sd (Eigen::MatrixBase< Derived > const &data)
	Sample standard deviation of a vector — sqrt(var(data)).
types::FeatureVector	ppforest2::stats::sd (types::FeatureMatrix const &data)
	Column-wise sample standard deviation — element-wise sqrt of var.
template<typename Y>
void	ppforest2::stats::sort (types::FeatureMatrix &x, Y &y)
	Sort a feature matrix and a response vector by the response values.
std::set< types::GroupId >	ppforest2::stats::unique (types::GroupIdVector const &column)
	Unique group labels in a response vector.
template<typename Derived>
double	ppforest2::stats::var (Eigen::MatrixBase< Derived > const &data)
	Sample variance of a vector (unbiased, n-1 denominator).
types::FeatureVector	ppforest2::stats::var (types::FeatureMatrix const &data)
	Column-wise sample variance of a matrix.