Real life datasets often suffer from the problem of class imbalance, which thwarts supervised learning process. In such data sets examples of positive (minority) class are signific...
—Real-world data mining deals with noisy information sources where data collection inaccuracy, device limitations, data transmission and discretization errors, or man-made pertur...
Abstract. In this paper we propose a new method to perform incremental discretization. The basic idea is to perform the task in two layers. The first layer receives the sequence o...
This paper describes a novel data mining approach that employs evolutionary programming to discover knowledge represented in Bayesian networks. There are two different approaches ...
Spatial clustering is an active research area in spatial data mining with various methods reported. In this paper, we compare two density-based methods, DBSCAN and DBRS. First, we ...