An innovative topic-based customer complaints sentiment classification system
Text mining helps to convert big text data into a small amount of most relevant data for a
particular problem, and also helps providing knowledge provenance and interpreting …
particular problem, and also helps providing knowledge provenance and interpreting …
Particle EM for variable selection
V Ročková - Journal of the American Statistical Association, 2018 - Taylor & Francis
Despite its long history of success, the EM algorithm has been vulnerable to local
entrapment when the posterior/likelihood is multi-modal. This is particularly pronounced in …
entrapment when the posterior/likelihood is multi-modal. This is particularly pronounced in …
Auto-summarization: A step towards unsupervised learning of a submodular mixture
We introduce an approach that requires the specification of only a handful of
hyperparameters to determine a mixture of submodular functions for use in data science …
hyperparameters to determine a mixture of submodular functions for use in data science …
DPP-VSE: Constructing a variable selection ensemble by determinantal point processes
As an effective tool to analyze high-dimensional data, variable selection is playing an
increasingly important role in many fields. In recent years, variable selection ensembles …
increasingly important role in many fields. In recent years, variable selection ensembles …
A lens into employee peer reviews via sentiment-aspect modeling
Given a corpus of employee peer reviews from a large corporation where each review is
structured into pros and cons, what are the prevalent traits that employees talk about? How …
structured into pros and cons, what are the prevalent traits that employees talk about? How …