Interpretability and accuracy issues in evolutionary multi-objective fuzzy classifiers
نویسندگان
چکیده
منابع مشابه
Handling High Dimensionality and Interpretability-Accuracy Trade-Off Issues in Evolutionary Multiobjective Fuzzy Classifiers
Fuzzy systems are capable to model the inherent uncertainties in real world problems and implement human decision making. In this paper two issues related to fuzzy systems development are addressed and solutions are proposed and implemented. First issue is related to the high dimensional data sets. Such kinds of data sets lead to explode the search space of generated rules and results into dete...
متن کاملA Review on the Interpretability-Accuracy Trade-Off in Evolutionary Multi-Objective Fuzzy Systems (EMOFS)
Interpretability and accuracy are two important features of fuzzy systems which are conflicting in their nature. One can be improved at the cost of the other and this situation is identified as “Interpretability-Accuracy Trade-Off”. To deal with this trade-off Multi-Objective Evolutionary Algorithms (MOEA) are frequently applied in the design of fuzzy systems. Several novel MOEA have been propo...
متن کاملAccuracy vs. Interpretability of Fuzzy Rule-Based Classifiers: An Evolutionary Approach
The paper presents a generalization of the Pittsburgh approach to learn fuzzy classification rules from data. The proposed approach allows us to obtain a fuzzy rule-based system with a predefined level of compromise between its accuracy and interpretability (transparency). The application of the proposed technique to design the fuzzy rule-based classifier for the well known benchmark data sets ...
متن کاملMulti–objective Evolutionary Optimization of Accuracy and Interpretability for Neuromuscular Blockade Control
We further investigate the relationship between accuracy and interpretability during the design of fuzzy systems. Both aspects are of major importance for the control of neuromuscular blockade. After describing how these goals can be measured, a multi-objective evolutionary optimization scheme is set up. The results show that even for the best optimization runs at the accuracy side of the Paret...
متن کاملImproving the accuracy while preserving the interpretability of fuzzy function approximators by means of multi-objective evolutionary algorithms
The identification of a model is one of the key issues in the field of fuzzy system modeling and function approximation theory. An important characteristic that distinguishes fuzzy systems from other techniques in this area is their transparency and interpretability. Especially in the construction of a fuzzy system from a set of given training examples, little attention has been paid to the ana...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Soft Computing and Networking
سال: 2016
ISSN: 2052-8450,2052-8469
DOI: 10.1504/ijscn.2016.077043