The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
An important investigation of time series involves searching for \movement" patterns, such as \going up" or \going down" or some combinations of them. Movement patt...
We propose in this paper an exploratory analysis algorithm for functional data. The method partitions a set of functions into K clusters and represents each cluster by a simple pr...
Abstract Irregularities are widespread in large databases and often lead to erroneous conclusions with respect to data mining and statistical analysis. For example, considerable bi...
Siu-Tong Au, Rong Duan, Siamak G. Hesar, Wei Jiang
— This paper presents clustering techniques (K-means, Fuzzy K-means, Subtractive) applied on specific databases (Flower Classification and Mackey-Glass time series) , to automati...
Juan E. Moreno, Oscar Castillo, Juan R. Castro, Lu...