Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
In this paper, we propose a novel probabilistic approach to summarize frequent itemset patterns. Such techniques are useful for summarization, post-processing, and end-user interp...
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...
For the discovery of similar patterns in 1D time-series, it is very typical to perform a normalization of the data (for example a transformation so that the data follow a zero mea...
High-dimensional data poses a severe challenge for data mining. Feature selection is a frequently used technique in preprocessing high-dimensional data for successful data mining....