vigra - BestGiniOfColumn< LineSearchLossTag > Class Template Reference

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| BestGiniOfColumn< LineSearchLossTag > Class Template Reference |

`#include <vigra/random_forest/rf_split.hxx>`

## Public Member Functions
template<class DataSourceF_t , class DataSource_t , class I_Iter , class Array >
void | operator() (DataSourceF_t const &column, DataSource_t const &labels, I_Iter &begin, I_Iter &end, Array const &region_response)

## Detailed Description

### template<class LineSearchLossTag>
class vigra::BestGiniOfColumn< LineSearchLossTag >

Given a column, choose a split that minimizes some loss

## Member Function Documentation

void operator() | ( | DataSourceF_t const & | column,
|  | DataSource_t const & | labels,
|  | I_Iter & | begin,
|  | I_Iter & | end,
|  | Array const & | region_response
| ) |  |

calculate the best gini split along a Feature Column

Parameters

  column | the feature vector - has to support the [] operator
  labels | the label vector
  begin |
  end | (in and out) begin and end iterators to the indices of the samples in the current region. the range begin - end is sorted by the column supplied during function execution.
  region_response | ??? class histogram of the range.

precondition: begin, end valid range, class_counts positive integer valued array with the class counts in the current range. labels.size() >= max(begin, end); postcondition: begin, end sorted by column given. min_gini_ contains the minimum gini found or NumericTraits<double>::max if no split was found. min_index_ contains the splitting index in the range or invalid data if no split was found. BestCirremtcounts[0] and [1] contain the class histogram of the left and right region of the left and right regions.

The documentation for this class was generated from the following file:

- vigra/random_forest/rf_split.hxx

© Ullrich Köthe (ullrich.koethe@iwr.uni-heidelberg.de) Heidelberg Collaboratory for Image Processing, University of Heidelberg, Germany | html generated using doxygen and Python vigra 1.11.0 (Fri May 19 2017)