In this paper, the power quality (PQ) disturbances have been detected and classified using Stockwell’s transform (S-transform) rule-based decision tree (DT) according to IEEE standards. The proposed technique based on extracted features of PQ events signals, which are from timefrequency analysis. Several considered with simple complex include spike, flicker, oscillatory transient, impulsive not...

Imbalanced classification problems are attracting the attention of research community because they prevalent in real-world and impose extra difficulties for learning methods. Fuzzy rule-based systems have been applied to cope with these problems, mostly together sampling techniques. In this paper, we define a new fuzzy association classifier, named FARCI, tackle directly imbalanced problems. Ou...

The automated recognition of the visual field defect type from results of visual field testing is crucial for the adequate diagnosis and treatment of the underlying disease of the visual system. This paper presents a reliable rule-based classifier that emulates the decision strategies of expert ophthalmologists based on a two-level approach that combines methods of unsupervised learning.

Rule based classification is one of the most popular way of classification in data mining. There are number of algorithms for rule based classification. C4.5 and Partial Decision Tree (PART) are very popular algorithms among them and both have many empirical features such as continuous number categorization, missing value handling, etc. However in many cases these algorithms takes more processi...

Phishing is described as the art of emulating a website of a creditable firm intending to grab user’s private information such as usernames, passwords and social security number. Phishing websites comprise a variety of cues within its content-parts as well as browser-based security indicators. Several solutions have been proposed to tackle phishing. Nevertheless, there is no single magic bullet...

Assessing rules with interestingness measures is the cornerstone of successful applications of association rule discovery. However, as numerous measures may be found in the literature, choosing the measures to be applied for a given application is a difficult task. In this chapter, the authors present a novel and useful classification of interestingness measures according to three criteria: the...

Introduction Processing Results Task Description input data: about 2000 mammography reports from 3 Warsaw hospitals, output data: (for each report) very detailed information concerning:

Chapter 1: INTRODUCTION Chapter 2: SHAPE-BASED DESCRIPTION 2.1 Fourier Descriptors 2.2 Moment Invariants 2.3 Scalar Descriptors Chapter 3: CLASSIFICATION 3.1 Supervised v Unsupervised Classification 3.2 Classification using Bayes Theorem 3.3 Implementing Bayesian Classification Chapter 4: COMBINING CLASSIFIERS 4.1 The Fusion Model 4.2 Theory 4.2.1 The Product Rule 4.2.2 Sum Rule 4.3 Classifier ...