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Mostrando ítems 1-4 de 4
Artículo
Kernel Penalized K-means: A feature selection method based on Kernel K-means
(ELSEVIER SCIENCE BV, 2015-11-20)
We present an unsupervised method that selects the most relevant features using an embedded strategy while maintaining the cluster structure found with the initial feature set. It is based on the idea of simultaneously ...
Artículo
Cost-sensitive feature selection for support vector machines
(Elsevier, 2018-03)
Feature Selection (FS) is a crucial procedure in Data Science tasks such as Classification, since it identifies the relevant variables, making thus the classification procedures more interpretable and more effective by ...
Artículo
Mixed integer linear programming for feature selection in support vector machine
(Elsevier, 2019)
This work focuses on support vector machine (SVM) with feature selection. A MILP formula- tion is proposed for the problem. The choice of suitable features to construct the separating hyperplanes has been modeled in this ...
Artículo
Variable selection in classification for multivariate functional data
(ELSEVIER SCIENCE INC, 2019-05-01)
When classification methods are applied to high-dimensional data, selecting a subset of the predictors may lead to an improvement in the predictive ability of the estimated model, in addition to reducing the model complexity. ...