Characterizing the shared memberships of individuals in a classification scheme poses severe interpretability issues, even when using a moderate number of classes (say 4). Mixed membership models quantify this phenomenon, but they typically focus on goodness-of-fit more than on interpretable inference.
Deciding on what constitutes a good model requires tradeoffs between statistical goodness-of-fit criteria and frequently non-quantifiable subject-matter-based ...
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Across mixed membership models, however, the assignments z are discrete and drawn from the proportions θ. Thus, all MMM need to work with a distribution over θ.
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When using a mixed membership model, the interest is typically in estimating the sub-population parameters θ, the Dirichlet parameter α and the latent ...
[PDF] Dimension-Grouped Mixed Membership Models for Multivariate ...
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Gro-M3 improves interpretability by allowing the potentially high-dimensional observed variables to belong to a small number of meaningful groups.
[PDF] Interpretability Constraints and Trade-offs in Using Mixed ...
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We show that by introducing separate mixed membership models, each containing a small number of ideal profiles, to describe a population according to responses ...
Multivariate mixed membership modeling: Inferring domain-specific ...
projecteuclid.org › 21-AOAS1496
Mar 28, 2022 · Mixed membership models quantify this phenomenon, but they typically focus on goodness-of-fit more than on interpretable inference. To achieve a ...
This work characterize extant contributions employing topic models in marketing along the dimensions data structures and retrieval of input data, ...
Oct 13, 2014 · It explores the use of the models in various application settings, including survey data, population genetics, text analysis, image processing ...
Nov 24, 2015 · We studied mixture models in detail, models that partition data into a collection of latent groups. We now discuss mixed-membership models, ...