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KDD
1995
ACM
135views Data Mining» more  KDD 1995»
13 years 8 months ago
Rough Sets Similarity-Based Learning from Databases
Manydata mining algorithms developed recently are based on inductive learning methods. Very few are based on similarity-based learning. However, similarity-based learning accrues ...
Xiaohua Hu, Nick Cercone
RSCTC
1993
Springer
161views Fuzzy Logic» more  RSCTC 1993»
13 years 8 months ago
Quantifying Uncertainty of Knowledge Discovered From Databases
This paper focuses on the application of rough set constructs to inductive learning from a database. A design guideline is suggested, which provides users the option to choose app...
Yang Xiang, S. K. Michael Wong, Nick Cercone
FUIN
2002
123views more  FUIN 2002»
13 years 4 months ago
Learning Rough Set Classifiers from Gene Expressions and Clinical Data
Biological research is currently undergoing a revolution. With the advent of microarray technology the behavior of thousands of genes can be measured simultaneously. This capabilit...
Herman Midelfart, Henryk Jan Komorowski, Kristin N...
INFORMATICALT
2008
162views more  INFORMATICALT 2008»
13 years 4 months ago
Vague Rough Set Techniques for Uncertainty Processing in Relational Database Model
Abstract. The study of databases began with the design of efficient storage and data sharing techniques for large amount of data. This paper concerns the processing of imprecision ...
Karan Singh, Samajh Singh Thakur, Mangi Lal
CVPR
2006
IEEE
13 years 10 months ago
Learning Non-Metric Partial Similarity Based on Maximal Margin Criterion
The performance of many computer vision and machine learning algorithms critically depends on the quality of the similarity measure defined over the feature space. Previous works...
Xiaoyang Tan, Songcan Chen, Jun Li, Zhi-Hua Zhou