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    • New Approaches To Photometric Redshift Prediction

    Metadata Updated: April 11, 2025

    Expanding upon the work of Way & Srivastava (2006) we demonstrate how the use of training sets of comparable size continue to make Gaussian Process Regression a competitive approach to that of Neural Networks and other least squares fitting methods. This is possible via new large size matrix inversion techniques developed for Gaussian Processes that do not require that the kernel matrix be sparse. This development, combined with a neural-network kernel function appears to give superior results for this problem. Our best t results for the Sloan Digital Sky Survey Main Galaxy Sample using u,g,r,i,z gives an rms error of 0.0201 while our results for the same in the Luminous Red Galaxy Sample yield 0.0220.

    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.

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    Dates

    Metadata Created Date November 12, 2020
    Metadata Updated Date April 11, 2025
    Data Update Frequency irregular

    Metadata Source

    Harvested from NASA Data.json

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date November 12, 2020
    Metadata Updated Date April 11, 2025
    Publisher Dashlink
    Maintainer
    Identifier DASHLINK_166
    Data First Published 2010-09-22
    Data Last Modified 2025-04-01
    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 64155cd8-d896-43b8-9390-4bdb3576297f
    Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
    Harvest Source Title NASA Data.json
    Homepage URL https://c3.nasa.gov/dashlink/resources/166/
    Program Code 026:029
    Source Datajson Identifier True
    Source Hash 775e2e91f0e420a19189b5a839bf338956157cc6abedb0ab4d6585aaab8169f5
    Source Schema Version 1.1

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