Feature Selection Toolbox FST4
UTIA · Czech Academy of Sciences
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criterion_normal_divergence.hpp File Reference

Implements Divergence (distance) based on normal (gaussian) model to serve as feature selection criterion. More...

#include <memory>
#include <cassert>
#include <iostream>
#include <cmath>
#include "error.hpp"
#include "global.hpp"
#include "criterion_normal.hpp"
#include "indexed_vector.hpp"
#include "indexed_matrix.hpp"

Go to the source code of this file.

Classes

class  FST::Criterion_Normal_Divergence< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR >
 Implements Divergence (distance) based on normal (gaussian) model to serve as feature selection criterion. More...

Namespaces

namespace  FST
 The Feature Selection Toolbox 4 library: every library component – data access, criteria and classifiers, search algorithms, result trackers and the global infrastructure – lives in this namespace.

Detailed Description

Implements Divergence (distance) based on normal (gaussian) model to serve as feature selection criterion.

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Feature Selection Toolbox 4 source code

Author
Petr Somol (somol.nosp@m.@uti.nosp@m.a.cas.nosp@m..cz) with collaborators, see Contacts at https://fst.utia.cz
Version 4 was developed with Anthropic Claude models as coding assistants: Claude Fable 5 for the 2026 development (with minor contributions by Claude Opus 5), Claude Fable 5.1 for the pre-publication reviews of the full codebase, and Claude Opus 4.5 for the December 2025 audit of the FST3 codebase; design, decisions, review and acceptance are human work
Date
October 2010 (last updated July 2026)
Version
4.2.0
Note
FST4 was developed using MinGW-W64 g++ 15.2 and requires
  • a C++17 conforming compiler and standard library (no Boost, unlike FST3),
Note that LibSVM is required for SVM related tools only. Ready-to-run SVM examples: demos/demo12t.cfg, demo23.cfg, demo25t.cfg and demo32t.cfg (configurations of the fst4 command-line tool).
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