Binary clustering

Binary clustering

In many clustering systems (hierarchies, pyramids and more generally weak hierarchies) clusters are generated by two elements only. This paper is devoted to such clustering systems (called binary clustering systems). It provides some basic properties, links with (closed) weak hierarchies and some qualitative versions of bijection theorems that occur in Numerical Taxonomy. Moreover, a way to ass...

On Clustering Binary Data

Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. This paper studies the problem of clustering binary data. This is the case for market basket datasets where the transactions contain items and for document datasets where the documents contain “bag of words”. The contributio...

Clustering in Interfering Binary Mixtures

Colloids are binary mixtures of molecules with one type of molecule suspended in another. It is believed that at low density typical configurations will be well-mixed throughout, while at high density they will separate into clusters. We characterize the high and low density phases for a general family of discrete interfering binary mixtures by showing that they exhibit a “clustering property” ...

Clustering of Sparse Binary Data

Clustering Binary Data with Bernoulli Mixture Models

Clustering is an unsupervised learning technique that seeks “natural” groupings in data. One form of data that has not been widely studied in the context of clustering is binary data. A rich statistical framework for clustering binary data is the Bernoulli mixture model for which there exists both Bayesian and non-Bayesian approaches. This paper reviews the development and application of Bernou...