The rough and fuzzy set approaches presented here open up many new frontiers for
continued research and development Computational Intelligence and Feature Selection …

The present article provides a survey of the available literature on data mining using soft
computing. A categorization has been provided based on the different soft computing tools …

Association rules are considered to be the best studied models for data mining. In this
article, we propose their use in order to extract knowledge so that normal behavior patterns …

The theory of fuzzy sets has been recognized as a suitable tool to model several kinds of
patterns that can hold in data. In this paper, we are concerned with the development of a …

This valuable text addresses different pattern recognition (PR) tasks in a unified framework
with both theoretical and experimental results. Tasks covered include data condensation …

One of the main obstacles facing current intelligent pattern recognition applications is that of
dataset dimensionality. To enable these systems to be effective, a redundancy-removing …

The generation of effective feature pattern-based classification rules is essential to the
development of any intelligent classifier which is readily comprehensible to the user. This …

In order to allow for the analysis of data sets including numerical attributes, several
generalizations of association rule mining based on fuzzy sets have been proposed in the …

The main aim of this paper is to present a revision of the most relevant results about the use
of Fuzzy Sets in Data Mining, specifically in relation with the discovery of Association Rules …

Feature selection (FS) refers to the problem of selecting those input attributes that are most
predictive of a given outcome; a problem encountered in many areas such as machine …