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Mostrando ítems 61-70 de 84
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 ...
A guided data projection technique for classi cation of sovereign ratings: the case of European Union 27
(2017-01-20)
Sovereign rating has had an increasing importance since the beginning of the
nancial crisis. However, credit rating agencies opacity has been criticised by
several authors highlighting the suitability of designing more ...
Trabajando con imágenes digitales en clase de Matemáticas
(Real Sociedad Matemática Española, 2010)
Una clase de aritmética modular, matrices y cifrado para Ingeniería
(Federación Iberoamericana de Educación Matemática (FISEM), 2011)
El Álgebra Lineal tiene una gran cantidad de aplicaciones sin embargo se suele
abordar casi siempre de una forma bastante abstracta a nivel universitario. Así que
para motivar a nuestro alumnado planificamos realizar ...