Building a high accuracy classifier for classification is a problem in real applications. One high accuracy classifier used for this purpose is based on association rules. In the past, some researches showed that classification based on association rules (or class-association rules – CARs) has higher accuracy than that of other rule-based methods, such as ILA and C4.5. However, mining CARs cons...

The determination of transformer fault categories using soft-computing based techniques has been the subject of much research in the recent past. The development of an adaptive fuzzy classifier which can effectively determine various classes or categories of series and shunt impulse faults in a wide range of power transformers is described. The system employs a self-generating module to automat...

This paper presents a design method for fuzzy rule-based systems that performs data modeling consistently according to the symbolic relations expressed by the rules. The focus of the model is the interpretability of the rules and the model’s accuracy, such that it can be used as tool for data understanding. The number of rules is defined by the eigenstructure analysis of the similarity matrix, ...

Due to its explicit modeling of the grammaticality of the output via target-side syntax, the string-to-tree model has been shown to be one of the most successful syntax-based translation models. However, a major limitation of this model is that it does not utilize any useful syntactic information on the source side. In this paper, we analyze the difficulties of incorporating source syntax in a ...

Linguistic decision tree (LDT) [7] is a classification model based on a random set based semantics which is referred to as label semantics [4]. Each branch of a trained LDT is associated with a probability distribution over classes. In this paper, two hybrid learning models by combining linguistic decision tree and fuzzy Naive Bayes classifier are proposed. In the first model, an unlabelled ins...

Article history: Available online 4 March 2011

We propose a fuzzy rule-based system to map representations of the emotional state of an animated agent onto muscle contraction values for the appropriate facial expressions. Our implementation pays special attention to the way in which continuous changes in the intensity of emotions can be displayed smoothly on the graphical face. The rule system we have defined implements the patterns describ...

1 Dental Diagnosis from X-Ray Images using Fuzzy Rule-Based Systems; Tran Manh Tuan, School of Information and Communication Technology, Thai Nguyen University, Thai Nguyen, Vietnam Nguyen Thanh Duc, Hanoi University of Science and Technology, Hanoi, Vietnam Pham Van Hai, Hanoi University of Science and Technology, Hanoi, Vietnam Le Hoang Son, VNU University of Science, Vietnam National Univers...

This research presents a system for post processing of data that takes mined flat rules as input and discovers crisp as well as fuzzy hierarchical structures using Learning Classifier System approach. Learning Classifier System (LCS) is basically a machine learning technique that combines evolutionary computing, reinforcement learning, supervised or unsupervised learning and heuristics to produ...

While larger and larger pools of stock market data are available for investors, it is crucial for them to achieve the knowledge hidden behind and make the correct selections. The huge data amount, the variable data characteristic, and the noisy environment make this goal a great challenge. Using the model of fuzzy decision tree based rules extraction, a new set of fuzzy rules to select stocks w...