Corrigendum to: Influence of fuzzy norms and other heuristics on "Mixed fuzzy rule formation" [Int. J. Approx. Reasoning 35 (2004) 195-202]
نویسندگان
چکیده
hereby correct an error in Ref. [2], in which we studied the influence of various parameters that affect the generalization performance of fuzzy models constructed using the mixed fuzzy rule formation method [1]. On page 196, the last equation that computes the normalized loss in volume V
منابع مشابه
Influence of fuzzy norms and other heuristics on "Mixed fuzzy rule formation"
In Mixed Fuzzy Rule Formation [Int. J. Approx. Reason. 32 (2003) 67] a method to extract mixed fuzzy rules from data was introduced. The underlying algorithm’s performance is influenced by the choice of fuzzy t-norm and t-conorm, and a heuristic to avoid conflicts between patterns and rules of different classes throughout training. In the following addendum to [Int. J. Approx. Reason. 32 (2003)...
متن کاملMixed fuzzy rule formation
Many fuzzy rule induction algorithms have been proposed during the past decade or so. Most of these algorithms tend to scale badly with large dimensions of the feature space and in addition have trouble dealing with different feature types or noisy data. In this paper, an algorithm is proposed that extracts a set of so called mixed fuzzy rules. These rules can be extracted from feature spaces w...
متن کاملTriple I algorithms based on Schweizer-Sklar operators in fuzzy reasoning
In this paper, the perturbation of fuzzy connectives and the robustness of fuzzy reasoning are investigated. This perturbation of Schweizer-Sklar parameterized t-norms and its residuated implication operators are given. We show that full implication triple I algorithms based on Schweizer-sklar operators are robust for normalized Minkowski distance.
متن کاملA genetic tuning to improve the performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets: Degree of ignorance and lateral position
Article history: Received 18 May 2010 Revised 24 January 2011 Accepted 27 January 2011 Available online 4 February 2011
متن کاملA proposal on reasoning methods in fuzzy rule-based classification systems
Fuzzy Rule-Based Systems have been succesfully applied to pattern classification problems. In this type of classification systems, the classical Fuzzy Reasoning Method (FRM) classifies anew example with the consequent of the rule with the greatest degree of association. By using this reasoning method, we lose the information provided by the other rules with different linguistic labels which als...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Int. J. Approx. Reasoning
دوره 47 شماره
صفحات -
تاریخ انتشار 2008