In this paper, we aim to improve the classification of human non-speech sounds produced in a meeting-room environment by using concepts and tools from the fuzzy theory. Starting with an SVM-based baseline system, firstly a reduction of the number of features with the fuzzy measure is shown. And, secondly, a noticeable improvement of the classification performance is reported by combining the ou...

Classification Rules (CRs) are often discovered in the form of ‘If-Then’ Production Rules (PRs). PRs, being high level symbolic rules, are comprehensible and easy to implement. However, they are not capable of dealing with cognitive uncertainties like vagueness and ambiguity imperative to real word decision making situations. Fuzzy Classification Rules (FCRs) based on fuzzy logic provide a fram...

Fuzzy rule based classification systems are one of the most popular fuzzy modeling systems used in pattern classification problems. This paper investigates the effect of applying nine different T-norms in fuzzy rule based classification systems. In the recent researches, fuzzy versions of confidence and support merits from the field of data mining have been widely used for both rules selecting ...

i n troduction: cancer is a major cause of mortality in the modern world, and one of the most important health problems in societies. during recent years, research on cancer as a system biology disease is focused on molecular differences between cancer cells and healthy cells. most of the proposed methods for classifying cancer using gene expression data act as black boxes and lack biological i...

In this paper, a new Hopfield-model net based on fuzzy possibilistic reasoning is proposed for the classification of multispectral images. The main purpose is to modify the Hopfield network embedded with fuzzy possibilistic -means (FPCM) method to construct a classification system named fuzzy-possibilistic Hopfield net (FPHN). The classification system is a paradigm for the implementation of fu...

Text mining techniques are generally applied for classifying the text, finding fuzzy relations and structures in data sets. This research provides plenty text mining capabilities. One common application is text classification and event extraction, which encompass deducing specific knowledge concerning incidents referred to in texts. The main contribution of this paper is the clarification of a ...

Artificial Immune Recognition System (AIRS) classification algorithm, which has an important place among classification algorithms in the field of Artificial Immune Systems, has showed an effective and intriguing performance on the problems it was applied. AIRS was previously applied to some medical classification problems including Breast Cancer, Cleveland Heart Disease, Diabetes and it obtain...

The applications of fuzzy logic and fuzzy algorithms to the classification of celestial objects will be explored through various prominent papers in the field. Specifically, these papers will address issues concerning star and galaxy separation, classification of stars into their spectral types, classification of galaxies into the main galaxy types, and comparing the results to their neural net...

In this study, we present a BCC detector based on confocal Raman spectroscopy using maximum a posteriori probability (MAP) and fuzzy algorithm. The preprocessing step consists of data normalization with minmax method and dimension reduction with principal components analysis (PCA). To enhance the classification performance, we divide Raman spectra into two significant protein bands, i.e., Amid ...

At present a great deal of research is being done in different aspects of Content-Based Image Retrieval (CBIR). Image classification is one of the most important tasks in image retrieval that must be dealt with. The primary issue we have addressed is: how can the fuzzy set theory be used to handle crisp image data. We propose fuzzy rule-based classification of image objects. To achieve this goa...