We introduce a framework for filtering features that employs the Hilbert-Schmidt Independence Criterion (HSIC) as a measure of dependence between the features and the labels. The ...
Le Song, Alex J. Smola, Arthur Gretton, Karsten M....
Low-rank matrix decompositions are essential tools in the application of kernel methods to large-scale learning problems. These decompositions have generally been treated as black...
- The aim of this paper is to propose a filter, based on a multi-objective evolutionary algorithm, for attributes’ ranking in the context of a data mining task. The behavior of t...
Daniela Zaharie, Stefan Holban, Diana Lungeanu, Da...
Support Vector Machines (SVMs) have been successfully applied to solve a large number of classification and regression problems. However, SVMs suffer from the catastrophic forgetti...
This paper uses the GP paradigm to evolve linear genotypes (individuals) that consist of Java byte code. Our prototype GP system is implemented in Java using a standard Java devel...