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» A Comparative Study of Fuzzy Sets and Rough Sets
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RSCTC
2010
Springer
142views Fuzzy Logic» more  RSCTC 2010»
15 years 4 months ago
Learning from Imbalanced Data in Presence of Noisy and Borderline Examples
In this paper we studied re-sampling methods for learning classifiers from imbalanced data. We carried out a series of experiments on artificial data sets to explore the impact of ...
Krystyna Napierala, Jerzy Stefanowski, Szymon Wilk
PRL
2002
67views more  PRL 2002»
15 years 5 months ago
A pseudo-nearest-neighbor approach for missing data recovery on Gaussian random data sets
Missing data handling is an important preparation step for most data discrimination or mining tasks. Inappropriate treatment of missing data may cause large errors or false result...
Xiaolu Huang, Qiuming Zhu
FGR
2008
IEEE
299views Biometrics» more  FGR 2008»
16 years 18 days ago
Face recognition with occlusions in the training and testing sets
Partial occlusions in face images pose a great problem for most face recognition algorithms. Several solutions to this problem have been proposed over the years – ranging from d...
Hongjun Jia, Aleix M. Martínez
CMG
2000
15 years 7 months ago
Comparing CPU Performance Between and Within Processor Families
Our study compares CPU performance on RISC and CISC uni and multiprocessors of varying speeds, and shows that the Instruction Set Architecture (ISA) style no longer matters. Our s...
Lee A. Butler, Travis Atkison, Ethan L. Miller
HIS
2008
15 years 7 months ago
Artificial Data Sets Based on Knowledge Generators: Analysis of Learning Algorithms Efficiency
This paper proposes a methodology to generate artificial data sets to evaluate the behavior of machine learning techniques. The methodology relies in the definition of a domain an...
Joaquin Rios-Boutin, Albert Orriols-Puig, Josep Ma...