frbs: Fuzzy Rule-Based Systems for Classification and Regression inR
نویسندگان
چکیده
منابع مشابه
Constructing fuzzy rule-based systems with the R package “frbs”
Fuzzy sets as proposed by Zadeh (1965) are a generalization of classical set theory, in which objects, instead of just being members of a set or not, have a gradual degree of membership. Fuzzy rule-based systems (FRBS) have been used in the past successfully in many applications. They are competitive methods for classification and regression, especially for complex problems. One of their leadin...
متن کاملA Margin-based Model with a Fast Local Searchnewline for Rule Weighting and Reduction in Fuzzynewline Rule-based Classification Systems
Fuzzy Rule-Based Classification Systems (FRBCS) are highly investigated by researchers due to their noise-stability and interpretability. Unfortunately, generating a rule-base which is sufficiently both accurate and interpretable, is a hard process. Rule weighting is one of the approaches to improve the accuracy of a pre-generated rule-base without modifying the original rules. Most of the pro...
متن کاملEffect of rule weights in fuzzy rule-based classification systems
This paper examines the effect of rule weights in fuzzy rule-based classification systems. Each fuzzy IF–THEN rule in our classification system has antecedent linguistic values and a single consequent class. We use a fuzzy reasoning method based on a single winner rule in the classification phase. The winner rule for a new pattern is the fuzzy IF–THEN rule that has the maximum compatibility gra...
متن کاملSmooth support vector learning for fuzzy rule-based classification systems
To design a fuzzy rule-based classification system (fuzzy classifier) with good generalization ability in a high dimensional feature space has been an active research topic for a long time. As a powerful machine learning approach for pattern recognition problems, support vector machine (SVM) is known to have good generalization ability. More importantly, an SVM can work very well on a high(or e...
متن کاملFuzzy Rule Based Systems for Gender Classification from Blog Data
Gender classification is a popular machine learning task, which has been involved in various application areas, such as business intelligence, access control and cyber security. In the context of information granulation, gender related information can be divided into three types, namely, biological information, vision based information and social network based information. In traditional machin...
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: Journal of Statistical Software
سال: 2015
ISSN: 1548-7660
DOI: 10.18637/jss.v065.i06