Feature Selection with Fuzzy Decision Reducts
نویسندگان
چکیده
In this paper, within the context of fuzzy rough set theory, we generalize the classical rough set framework for data-based attribute selection and reduction, based on the notion of fuzzy decision reducts. Experimental analysis confirms the potential of the approach.
منابع مشابه
Attribute selection with fuzzy decision reducts
Rough set theory provides a methodology for data analysis based on the approximation of concepts in information systems. It revolves around the notion of discernibility: the ability to distinguish between objects, based on their attribute values. It allows to infer data dependencies that are useful in the fields of feature selection and decision model construction. In many cases, however, it is...
متن کاملIntelligent decision support system based on rough set and fuzzy logic approach for efficacious precipitation forecast
Article history: Received February 25, 2016 Received in revised format: March 28, 2016 Accepted June 26, 2016 Available online June 26 2016 Weather forecasting is essential and demanding scientific task of meteorological services across the world. It is a complex procedure that includes many specific technological field of study. The prediction is intricate process in meteorology because all de...
متن کاملDominance-based Rough Interval-valued Fuzzy Set in Incomplete Fuzzy Information System
The fuzzy rough set is a fuzzy generalization of the classical rough set. In the traditional fuzzy rough model, the set to be approximated is a fuzzy set. This paper deals with an incomplete fuzzy information system with interval-valued decision by means of generalizing the rough approximation of a fuzzy set to the rough approximation of an interval-valued fuzzy set. Since all condition attribu...
متن کاملVisual analysis of relevant features in Customer Loyalty Improvement Recommendation
This chapter describes a practical area of application of decision reducts to a real-life business problem. It presents a feature selection (attribute reduction) methodology based on the decision reducts theory, which is supported by a designed and developed visualization system. The chapter overviews an application area Customer Loyalty Improvement Recommendation, which has become a very popul...
متن کاملSemi-Supervised Fuzzy-Rough Feature Selection
With the continued and relentless growth in dataset sizes in recent times, feature or attribute selection has become a necessary step in tackling the resultant intractability. Indeed, as the number of dimensions increases, the number of corresponding data instances required in order to generate accurate models increases exponentially. Fuzzy-rough set-based feature selection techniques offer gre...
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:
دوره شماره
صفحات -
تاریخ انتشار 2008