Fuzzy feature selection
نویسندگان
چکیده
In fuzzy classi"er systems the classi"cation is obtained by a number of fuzzy If}Then rules including linguistic terms such as Low and High that fuzzify each feature. This paper presents a method by which a reduced linguistic (fuzzy) set of a labeled multi-dimensional data set can be identi"ed automatically. After the projection of the original data set onto a fuzzy space, the optimal subset of fuzzy features is determined using conventional search techniques. The applicability of this method has been demonstrated by reducing the number of features used for the classi"cation of four real-world data sets. This method can also be used to generate an initial rule set for a fuzzy neural network. ( 1999 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
منابع مشابه
Fuzzy-rough Information Gain Ratio Approach to Filter-wrapper Feature Selection
Feature selection for various applications has been carried out for many years in many different research areas. However, there is a trade-off between finding feature subsets with minimum length and increasing the classification accuracy. In this paper, a filter-wrapper feature selection approach based on fuzzy-rough gain ratio is proposed to tackle this problem. As a search strategy, a modifie...
متن کاملA hybrid filter-based feature selection method via hesitant fuzzy and rough sets concepts
High dimensional microarray datasets are difficult to classify since they have many features with small number ofinstances and imbalanced distribution of classes. This paper proposes a filter-based feature selection method to improvethe classification performance of microarray datasets by selecting the significant features. Combining the concepts ofrough sets, weighted rough set, fuzzy rough se...
متن کاملNeuro-Fuzzy Based Algorithm for Online Dynamic Voltage Stability Status Prediction Using Wide-Area Phasor Measurements
In this paper, a novel neuro-fuzzy based method combined with a feature selection technique is proposed for online dynamic voltage stability status prediction of power system. This technique uses synchronized phasors measured by phasor measurement units (PMUs) in a wide-area measurement system. In order to minimize the number of neuro-fuzzy inputs, training time and complication of neuro-fuzzy ...
متن کاملA Classification Method for E-mail Spam Using a Hybrid Approach for Feature Selection Optimization
Spam is an unwanted email that is harmful to communications around the world. Spam leads to a growing problem in a personal email, so it would be essential to detect it. Machine learning is very useful to solve this problem as it shows good results in order to learn all the requisite patterns for classification due to its adaptive existence. Nonetheless, in spam detection, there are a large num...
متن کاملEffective Feature Selection for Pre-Cancerous Cervix Lesions Using Artificial Neural Networks
Since most common form of cervical cancer starts with pre-cancerous changes, a flawless detection of these changes becomes an important issue to prevent and treat the cervix cancer. There are 2 ways to stop this disease from developing. One way is to find and treat pre-cancers before they become true cancers, and the other is to prevent the pre-cancers in the first place. The presented approach...
متن کاملApplication of Fuzzy-rough Set Theory for Feature Subset Selection
Fuzzy Set Theory and Rough Set Theory are the most popular mathematical tools for dealing with uncertainties. During past decades, these set theories are being applied successfully in several areas for solving many complex tasks. This paper is concerned with the application of hybrid Fuzzy-Rough set based approach for feature subset selection. Keywords— Fuzzy set theory, Rough Set theory, Fuzzy...
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:
- Pattern Recognition
دوره 32 شماره
صفحات -
تاریخ انتشار 1999