Clustering categories in support vector machines
Year of publication: |
January 2017
|
---|---|
Authors: | Carrizosa, Emilio ; Nogales-Gómez, Amaya ; Romero Morales, María Dolores |
Published in: |
Omega : the international journal of management science. - Oxford [u.a.] : Elsevier, ISSN 0305-0483, ZDB-ID 124502-8. - Vol. 66.2017, part a, p. 28-37
|
Subject: | Support vector machine | Categorical features | Classifier sparsity | Clustering | Quadratically constrained programming | 0-1 programming | Regionales Cluster | Regional cluster | Mustererkennung | Pattern recognition | Klassifikation | Classification |
-
Machine learning-based classifiers ensemble for credit risk assessment
Pandey, Trilok Nath, (2013)
-
Alyami, Sarah N., (2020)
-
Accuracy analysis of various classification algorithms for used land
Kumar, N. Suresh, (2016)
- More ...
-
Heuristic Approaches for Support Vector Machines with the Ramp Loss
Carrizosa, Emilio, (2014)
-
Strongly Agree or Strongly Disagree?: Rating Features in Support Vector Machines
Carrizosa, Emilio, (2013)
-
p-facility Huff location problem on networks
Blanquero, Rafael, (2016)
- More ...