Assessing the quality of discovered results is an important open problem in data mining. Such assessment is particularly vital when mining itemsets, since commonly many of the disc...
In the Bayesian mixture modeling framework it is possible to infer the necessary number of components to model the data and therefore it is unnecessary to explicitly restrict the n...
Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an 1-regularized linear regression prob...
Recently, a variety of workflow patterns has been proposed focusing on specific aspects like control flow, data flow, and resource assignments. Though these patterns are relevant f...
We present a Two-Stage Machine Learning (ML) model as a data mining method to develop practice guidelines and apply it to the problem of dementia staging. Dementia staging in clin...
Subramani Mani, William Rodman Shankle, Malcolm B....