Domains of competence of fuzzy rule based classification systems with data complexity measures: A case of study using a fuzzy hybrid genetic based machine learning method

2010 ◽  
Vol 161 (1) ◽  
pp. 3-19 ◽  
Author(s):  
Julián Luengo ◽  
Francisco Herrera
Keyword(s):  
Machine Learning ◽  
Fuzzy Rule ◽  
Classification Systems ◽  
Machine Learning Method ◽  
Data Complexity ◽  
Learning Method ◽  
Complexity Measures ◽  
Rule Based

scholarly journals Design of Fuzzy Rule-based Classifiers through Granulation and Consolidation

2017 ◽  
Vol 7 (2) ◽  
pp. 137-147 ◽  
Author(s):  
Andri Riid ◽  
Jürgo-Sören Preden
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Fuzzy Rule ◽  
Complexity Reduction ◽  
Error Reduction ◽  
Classification Systems ◽  
Classification Problems ◽  
Rule Based ◽  
Classification Approach ◽  
Good Balance

AbstractThis paper addresses the issue how to strike a good balance between accuracy and compactness in classification systems - still an important question in machine learning and data mining. The fuzzy rule-based classification approach proposed in current paper exploits the method of rule granulation for error reduction and the method of rule consolidation for complexity reduction. The cooperative nature of those methods - the rules are split in a way that makes efficient rule consolidation feasible and rule consolidation itself is capable of further error reduction - is demonstrated in a number of experiments with nine benchmark classification problems. Further complexity reduction, if necessary, is provided by rule compression.

Speech Organ Contour Extraction Using Real-Time MRI and Machine Learning Method

2019 ◽  
Author(s):  
Hironori Takemoto ◽  
Tsubasa Goto ◽  
Yuya Hagihara ◽  
Sayaka Hamanaka ◽  
Tatsuya Kitamura ◽  
...  
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Machine Learning Method ◽  
Learning Method ◽  
Contour Extraction
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