Bayesian bi-clustering of categorical data
Extract textual information from Amazon products reviews and draw correlations through regression and fluctuation analysis.
Subspace clustering and coclustering course at the School of Electrical and Computer Engineering (FEEC-UNICAMP)
Directional Co-clustering with a Conscience (DCC)
Co-clustering algorithms can seek homogeneous sub-matrices into a dyadic data matrix, such as a document-word matrix.
Scala implementation of the Multiple Coclustering model, a Bayesian Non-Parametric method for block clustering of multivariate continuous observations
Co-clustering, also known as biclustering or block clustering, is a powerful data analysis technique that uncovers hidden structures in complex datasets.
We unified some latent block models by proposing a flexible ELBM that is extended to SELBM to address the sparse problem by revealing a diagonal structure from sparse datasets. This leads to obtain more homogeneous co-clusters and therefore produce useful, ready-to-use and easy-to-interpret results.
Clustering Algorithms in Python
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