main/cpp/ConfusionMatrix_8hpp_source.html

#pragma once


#include "utils/Types.hpp"


#include <map>


namespace ppforest2::stats {

  std::map<int, int> get_labels_map(types::ResponseVector const& groups);


  struct ConfusionMatrix {

    types::Matrix<int> values;

    std::map<int, int> label_index;


    ConfusionMatrix() = default;


    ConfusionMatrix(types::ResponseVector const& predictions, types::ResponseVector const& actual);


    types::Vector<float> group_errors() const;


    float error() const;

  };


}


Types.hpp

ppforest2::stats
Statistical infrastructure for training and evaluation.
Definition ConfusionMatrix.hpp:11

ppforest2::stats::get_labels_map
std::map< int, int > get_labels_map(types::ResponseVector const &groups)
Build a sorted mapping from unique group labels to contiguous indices.

ppforest2::types::ResponseVector
Eigen::Matrix< Response, Eigen::Dynamic, 1 > ResponseVector
Dynamic-size column vector of group labels.
Definition Types.hpp:29

ppforest2::types::Vector
Eigen::Matrix< T, Eigen::Dynamic, 1 > Vector
Generic dynamic-size column vector.
Definition Types.hpp:35

ppforest2::types::Matrix
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > Matrix
Generic dynamic-size matrix.
Definition Types.hpp:32

ppforest2::stats::ConfusionMatrix::values
types::Matrix< int > values
The NxN confusion matrix (actual x predicted).
Definition ConfusionMatrix.hpp:35

ppforest2::stats::ConfusionMatrix::ConfusionMatrix
ConfusionMatrix()=default
Default-construct an empty confusion matrix.

ppforest2::stats::ConfusionMatrix::group_errors
types::Vector< float > group_errors() const
Compute per-group error rates.

ppforest2::stats::ConfusionMatrix::label_index
std::map< int, int > label_index
Map from group label to matrix row/column index.
Definition ConfusionMatrix.hpp:36

ppforest2::stats::ConfusionMatrix::error
float error() const
Compute the overall error rate (1 - accuracy).

ppforest2::stats::ConfusionMatrix::ConfusionMatrix
ConfusionMatrix(types::ResponseVector const &predictions, types::ResponseVector const &actual)
Construct a confusion matrix from predictions and actual labels.