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Mixture Density Mercer Kernels

Metadata Updated: April 10, 2025

We present a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density estimate. We show how to convert the ensemble estimates into a Mercer Kernel, describe the properties of this new kernel function, and give examples of the performance of this kernel on unsupervised clustering of synthetic data and also in the domain of unsupervised multispectral image understanding.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

Downloads & Resources

Dates

Metadata Created Date November 12, 2020
Metadata Updated Date April 10, 2025
Data Update Frequency irregular

Metadata Source

Harvested from NASA Data.json

Additional Metadata

Resource Type Dataset
Metadata Created Date November 12, 2020
Metadata Updated Date April 10, 2025
Publisher Dashlink
Maintainer
Identifier DASHLINK_118
Data First Published 2010-09-10
Data Last Modified 2025-03-31
Public Access Level public
Data Update Frequency irregular
Bureau Code 026:00
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id d8cd892a-06cc-49f5-9eff-65abe774f41f
Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
Harvest Source Title NASA Data.json
Homepage URL https://c3.nasa.gov/dashlink/resources/118/
Program Code 026:029
Source Datajson Identifier True
Source Hash 8a260001a96c051a8daa365b25a7bf439bb6e5ef8565504ece3c51b09354fa8b
Source Schema Version 1.1

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