Bayesian mixture models and their Big Data implementations with application to invasive species presence-only data

Bayesian mixture models and their Big Data implementations with application to invasive species presence-only data

Abstract Due to their conceptual simplicity and flexibility, non-parametric mixture models are widely used to identify latent clusters in data. However, when it comes to Big Data, such as Landsat imagery, such model fitting is computationally prohibitive. To overcome this issue, we fit Bayesian non-...

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Bibliographic Details
Main Authors: Insha Ullah, Kerrie Mengersen
Format: Article
Language:English
Published: SpringerOpen 2019-03-01
Series:Journal of Big Data
Subjects:
Dirichlet process mixture models
k-means clustering
Tree-based clustering
Satellite imagery data
Fire-ants habitat
One-class support vector machine
Online Access:http://link.springer.com/article/10.1186/s40537-019-0188-1

Internet

http://link.springer.com/article/10.1186/s40537-019-0188-1

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