classifier_rbf_svm.hpp File Reference

Defines Classifier_RBF_SVM — dependency-free RBF kernel SVM (kernel dual coordinate descent) for wrapper-based feature selection. More...

#include <memory>
#include <vector>
#include <cmath>
#include <limits>
#include <cassert>
#include <iostream>
#include <sstream>
#include "error.hpp"
#include "global.hpp"
#include "dense_train_tools.hpp"
#include "clonable.hpp"
#include "classifier.hpp"
#include "fst_rand.hpp"

Go to the source code of this file.

Classes
class	FST::Classifier_RBF_SVM< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR >
	Dependency-free RBF kernel SVM trained by kernel dual coordinate descent (implemented from scratch, no LibSVM code; C-SVC with the RBF kernel only, deliberately NOT a LibSVM replacement: no nu-variants, no SVR, no one-class, no probability estimates, no shrinking). 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

Defines Classifier_RBF_SVM — dependency-free RBF kernel SVM (kernel dual coordinate descent) for wrapper-based feature selection.

======================================================================

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

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),

• (optionally) LibSVM (http://www.csie.ntu.edu.tw/~cjlin/libsvm/, version 3.37; not distributed with FST4 — drop svm.cpp/svm.h into ./libsvm/, see libsvm/readme.txt)

Note that LibSVM is required for SVM related tools only.