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Mostrando ítems 11-20 de 31
JCLEC Meets WEKA!
(2014-02-27)
WEKA has recently become a very referenced DM tool. In
spite of all the functionality it provides, it does not include any framework
for the development of evolutionary algorithms. An evolutionary
computation framework ...
A Classification Module for Genetic Programming Algorithms in JCLEC
(MIT Press, 2014)
JCLEC-Classi cation is a usable and extensible open source library for genetic program-
ming classi cation algorithms. It houses implementations of rule-based methods for clas-
si cation based on genetic programming, ...
Sistema de consulta de notas a través de Páginas Web y de Telefonía Móvil
(Universidad de Córdoba, Vicerrectorado de Innovación y Calidad Docente, 2005)
In this paper we are going to present a system which lets any student at Cordoba University knows what the final qualifications he has obtained in the different subjects he is registered are. The sytem lets him consult the ...
Sistemas de evaluación de los alumnos mediante test informatizados utilizando telefonía móvil
(Universidad de Córdoba, Vicerrectorado de Innovación y Calidad Docente, 2007)
This paper describes a system for executing adaptive tests in mobile devices. Tests are generated in XML files using Test Editor that is a author tool integrated in AHA! system. These tests are interpreted by our system ...
ur-CAIM: Improved CAIM Discretization for Unbalanced and Balanced Data
(2015-10-15)
Supervised discretization is one of basic data preprocessing
techniques used in data mining. CAIM (Class-
Attribute InterdependenceMaximization) is a discretization
algorithm of data for which the classes are known. ...
Parallel evaluation of Pittsburgh rule-based classifiers on GPUs
(2017-01-19)
Individuals from Pittsburgh rule-based classifiers represent a complete solution
to the classification problem and each individual is a variable-length set
of rules. Therefore, these systems usually demand a high level ...
Speeding up Multiple Instance Learning Classification Rules on GPUs
(2017)
Multiple instance learning is a challenging task in supervised learning and data mining. How-
ever, algorithm performance becomes slow when learning from large-scale and high-dimensional data sets.
Graphics processing ...
Scalable CAIM Discretization on Multiple GPUs Using Concurrent Kernels
(2017)
CAIM(Class-Attribute InterdependenceMaximization) is one of the stateof-
the-art algorithms for discretizing data for which classes are known. However, it
may take a long time when run on high-dimensional large-scale ...
Speeding Up Evolutionary Learning Algorithms using GPUs
(ESTYLF, 2010)
This paper propose a multithreaded Genetic
Programming classi cation evaluation model
using NVIDIA CUDA GPUs to reduce the
computational time due to the poor perfor-
mance in large problems. Two di erent clas-
si ...