The purpose of the work described in this paper is to provide an intelligent intrusion detection system (IIDS) that uses two of the most popular data mining tasks, namely classification and association rules mining together for predicting different behaviors in networked computers. To achieve this, we propose a method based on iterative rule learning using a fuzzy rule-based genetic classifier....

Department of Computer Science & Engineering/Shriram College of Engineering & Management [SRCEM] Banmore, Gwalior (MP)/India, 474003 _______________________________________________________________________________________ Abstract: Data mining is sorting through data to identify patterns and establish relationships. Association rule mining is a well established method of data mining that identif...

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 literature. While the formal specification of fuzzy associations is more or less straightforward, the assessment of such rules by means of appropriate quality measures is less obvious. Particularly, it assumes an underst...

This paper proposes a framework for mining market basket data to generate Nutritional Patterns (NPs) and a method for analysing generated nutritional patterns using Fuzzy Association Rule Mining. Edible attributes are filtered from transactional input data by projections and are then converted to Required Daily Allowance (RDA) numeric values. The RDA database is...

Association rule mining has wide variety of research in the field of data mining, many of association rule mining approaches are well investigated in literature, but the major issue with ARM is, huge number of frequent patterns cannot produce direct knowledge or factual knowledge, hence to find factual knowledge and to discover inference, we propose a novel approach AFIRM in this paper followed...

Fuzzy association rule mining discovers patterns in transactions, such as shopping baskets in a supermarket, or Web page accesses by a visitor to a Web site. Temporal patterns can be present in fuzzy association rules because the underlying process generating the data can be dynamic. However, existing solutions may not discover all interesting patterns because of a previously unrecognised probl...

Aiming at high overshoot and steady-state error in fuzzy controller of underwater vehicles, a new method based on data mining technique was presented. Apply Boolean association rule data mining to mine the polling list of fuzzy control from the database of manual operation record, and simulation and outfield experiments were carried out on Super Mohawk underwater vehicle to verify the feasibili...

Multi-objective evolutionary algorithms represent an effective tool to improve the accuracyinterpretability trade-off of fuzzy rule-based classification systems. To this aim, a tuning process and a rule selection process can be combined to obtain a set of solutions with different trade-offs between the accuracy and the compactness of models. Nevertheless, an initial model needs to be defined, i...

In this paper we propose an effective and efficient new Fuzzy Healthy Association Rule Mining Algorithm (FHARM) that produces more interesting and quality rules by introducing new quality measures. In this approach, edible attributes are filtered from transactional input data by projections and are then converted to Required Daily Allowance (RDA) numeric values. The averaged RDA database is the...