A nested heuristic for parameter tuning in Support Vector Machines
Year of publication: |
2014
|
---|---|
Authors: | Carrioza, Emilio ; Martín-Barragán, Belén ; Romero Morales, María Dolores |
Published in: |
Computers & operations research : and their applications to problems of world concern ; an international journal. - Oxford [u.a.] : Elsevier, ISSN 0305-0548, ZDB-ID 194012-0. - Vol. 43.2014, p. 328-334
|
Subject: | Supervised classification | Support Vector Machines | Parameter tuning | Nested heuristic | Variable neighborhood search | Multiple kernel learning | Mustererkennung | Pattern recognition | Heuristik | Heuristics | Theorie | Theory | Klassifikation | Classification | Algorithmus | Algorithm | Scheduling-Verfahren | Scheduling problem | Clusteranalyse | Cluster analysis | Prognoseverfahren | Forecasting model |
-
Adapting support vector optimisation algorithms to textual gender classification
Gomez, Javier, (2024)
-
Algorithms for multiclass classification and regularized regression
Burg, Gerrit Jan Johannes van den, (2018)
-
Convex optimization for group feature selection in networked data
Won, Daehan, (2020)
- More ...
-
Detecting relevant variables and interactions in supervised classification
Carrizosa, Emilio, (2011)
-
On sparse ensemble methods : an application to short-term predictions of the evolution of COVID-19
Benítez-Peña, Sandra, (2021)
-
A dissimilarity-based approach for Classification
Carrizosa, Emilio, (2005)
- More ...