Classification is an important task in data mining and machine learning which has been studied extensively and has a wide range of applications. There are many classification problem occurs and need to be solved. There are different types of classification algorithms like tree-based, rule-based etc, are widely used. In this paper, a performance comparison of different rule-based classifiers acr...

A fuzzy rule-based classification system (FRBCS) is one of the most popular approaches used in pattern classification problems. One advantage of a fuzzy rule-based system is its interpretability. However, we're faced with some challenges when generating the rule-base. In high dimensional problems, we can not generate every possible rule with respect to all antecedent combinations. In this paper...

We consider two classification approaches. The metric-based approach induces the distance measure between objects and classifies new objects on the basis of their nearest neighbors in the training set. The rule-based approach extracts rules from the training set and uses them to classify new objects. In the paper we present a model that combines both approaches. In the combined model the notion...

Intrusion detection system is used to identify anomalous packets in network. It can also identify unauthorized, malicious activity and malicious code in network. Currently, differnet apporaches of network intrusion detection systems are proposed by researchers. The classification based techniques has some issues such as model overfitting and classification evaluation. The challenging task in in...

In this work we study the behaviour of a Fuzzy Rule Based Classification System, and its relationship to a certain data complexity measures family. As Fuzzy Rule Based Classification System we have selected a recent proposal called Positive Definite Fuzzy Classifier, which is a Fuzzy System that uses Support Vector Machines for its training, obtaining accurate results and a low number of rules....

Classification aims to assign a data object to its appropriate class, what is traditionally performed through a small dataset model such as decision tree. Associative classification is a novel strategy for performing this task where the model is composed of a particular set of association rules, in which the consequent of each rule (i.e., its right-hand-side) is restricted to the classification...

Classification based on multiple dimensions of stimuli is usually associated with similarity-based representations, whereas uni-dimensional classifications are associated with rule-based representations. This paper studies classification of stimuli and category representations in school-aged children and adults when learning to categorize compound, multi-dimensional stimuli. Stimuli were such t...

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...