\( \newcommand{\E}{\mathrm{E}} \) \( \newcommand{\A}{\mathrm{A}} \) \( \newcommand{\R}{\mathrm{R}} \) \( \newcommand{\N}{\mathrm{N}} \) \( \newcommand{\Q}{\mathrm{Q}} \) \( \newcommand{\Z}{\mathrm{Z}} \) \( \def\ccSum #1#2#3{ \sum_{#1}^{#2}{#3} } \def\ccProd #1#2#3{ \sum_{#1}^{#2}{#3} }\)
CGAL 4.12.1 - Classification

Useful data structures that are used to compute features (computation of eigenvalues, for example) and to regularize classification (neighborhood).

Classes

class  CGAL::Classification::Evaluation
 Class to compute several measurements to evaluate the quality of a classification output. More...
 
class  CGAL::Classification::Point_set_neighborhood< GeomTraits, PointRange, PointMap >
 Class that precomputes spatial searching structures for an input point set and gives access to the local neighborhood of a point as a set of indices. More...
 
class  CGAL::Classification::Point_set_feature_generator< GeomTraits, PointRange, PointMap, ConcurrencyTag, DiagonalizeTraits >
 Generates a set of generic features for point set classification. More...
 
class  CGAL::Classification::Local_eigen_analysis
 Class that precomputes and stores the eigenvectors and eigenvalues of the covariance matrices of all points of a point set using a local neighborhood. More...
 
class  CGAL::Classification::Planimetric_grid< GeomTraits, PointRange, PointMap >
 Class that precomputes a 2D planimetric grid. More...