Learning rules from incomplete training examples by rough sets
TP Hong, LH Tseng, SL Wang - Expert Systems with Applications, 2002 - Elsevier
Machine learning can extract desired knowledge from existing training examples and ease
the development bottleneck in building expert systems. Most learning approaches derive …
the development bottleneck in building expert systems. Most learning approaches derive …
Learning a coverage set of maximally general fuzzy rules by rough sets
Expert systems have been widely used in domains where mathematical models cannot be
easily built, human experts are not available or the cost of querying an expert is high …
easily built, human experts are not available or the cost of querying an expert is high …
Mining from incomplete quantitative data by fuzzy rough sets
Machine learning can extract desired knowledge from existing training examples and ease
the development bottleneck in building expert systems. Most learning approaches derive …
the development bottleneck in building expert systems. Most learning approaches derive …
Learning cross-level certain and possible rules by rough sets
TP Hong, CE Lin, JH Lin, SL Wang - Expert Systems with Applications, 2008 - Elsevier
Machine learning can extract desired knowledge and ease the development bottleneck in
building expert systems. Among the proposed approaches, deriving rules from training …
building expert systems. Among the proposed approaches, deriving rules from training …
Fuzzy rough sets with hierarchical quantitative attributes
TP Hong, YL Liou, SL Wang - Expert systems with Applications, 2009 - Elsevier
Machine learning can extract desired knowledge and ease the development bottleneck in
building expert systems. Among the proposed approaches, deriving classification rules from …
building expert systems. Among the proposed approaches, deriving classification rules from …
Mining fuzzy β-certain and β-possible rules from quantitative data based on the variable precision rough-set model
TP Hong, TT Wang, SL Wang - Expert Systems with Applications, 2007 - Elsevier
The rough-set theory proposed by Pawlak, has been widely used in dealing with data
classification problems. The original rough-set model is, however, quite sensitive to noisy …
classification problems. The original rough-set model is, however, quite sensitive to noisy …
Classification of power system operation point using rough set techniques
G Lambert-Torres, APA Da Silva… - … on Systems, Man …, 1996 - ieeexplore.ieee.org
During the operation of a power system, the system operator is supplied with many data.
These data come from measurements into the system or from computational processes. The …
These data come from measurements into the system or from computational processes. The …
Knowledge acquisition from quantitative data using the rough-set theory
TP Hong, TT Wang, SL Wang - Intelligent Data Analysis, 2000 - content.iospress.com
Abstract Machine learning and data mining can extract desired knowledge or interesting
patterns from existing databases and ease the development bottleneck in building expert …
patterns from existing databases and ease the development bottleneck in building expert …
Learning coverage rules from incomplete data based on rough sets
In this paper, we deal with the problem of producing a set of certain and possible rules for
coverage of incomplete data sets based on rough sets. All the coverage rules gathered …
coverage of incomplete data sets based on rough sets. All the coverage rules gathered …
Learning fuzzy rules from incomplete quantitative data by rough sets
In this paper, we deal with the problem of learning from incomplete quantitative data sets
based on rough sets. Quantitative values are first transformed into fuzzy sets of linguistic …
based on rough sets. Quantitative values are first transformed into fuzzy sets of linguistic …