We present in this paper a modification of Lumer and Faieta’s algorithm for data clustering. This algorithm discovers automatically clusters in numerical data without prior kno...
Abstract. Analysis of data without labels is commonly subject to scrutiny by unsupervised machine learning techniques. Such techniques provide more meaningful representations, usef...
We investigate how random projection can best be used for clustering high dimensional data. Random projection has been shown to have promising theoretical properties. In practice,...
Clustering algorithms conduct a search through the space of possible organizations of a data set. In this paper, we propose two types of instance-level clustering constraints ? mu...
Whole genome comparison based on gene order has become a popular approach in comparative genomics. An important task in this field is the detection of gene clusters, i.e. sets of g...