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#unmixing — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #unmixing, aggregated by home.social.

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  1. I added several figures (3-6 through 3-9) to Part 3 of my unmixing posts, to better illustrate the performance of consensus interpretation methods.

    Part 3: dblog.vitumbre.tech/dart/unmix

    #Unmixing #NMF

  2. I added several figures (3-6 through 3-9) to Part 3 of my unmixing posts, to better illustrate the performance of consensus interpretation methods.

    Part 3: dblog.vitumbre.tech/dart/unmix

    #Unmixing #NMF

  3. I added several figures (3-6 through 3-9) to Part 3 of my unmixing posts, to better illustrate the performance of consensus interpretation methods.

    Part 3: dblog.vitumbre.tech/dart/unmix

    #Unmixing #NMF

  4. I added several figures (3-6 through 3-9) to Part 3 of my unmixing posts, to better illustrate the performance of consensus interpretation methods.

    Part 3: dblog.vitumbre.tech/dart/unmix

    #Unmixing #NMF

  5. I added several figures (3-6 through 3-9) to Part 3 of my unmixing posts, to better illustrate the performance of consensus interpretation methods.

    Part 3: dblog.vitumbre.tech/dart/unmix

    #Unmixing #NMF

  6. RE: floss.social/@rdnielsen/116365

    The third and last of the series on unmixing using NMF is now posted at

    dblog.vitumbre.tech/dart/unmix

    Part 3 illustrates the variability of results that can occur when repeatedly unmixing the same data set, and presents approaches to addressing the resultant uncertainty.

    #DataAnalysis #DataExploration #Unmixing #NMF #Python #JuliaLang #RStats

  7. RE: floss.social/@rdnielsen/116365

    The third and last of the series on unmixing using NMF is now posted at

    dblog.vitumbre.tech/dart/unmix

    Part 3 illustrates the variability of results that can occur when repeatedly unmixing the same data set, and presents approaches to addressing the resultant uncertainty.

    #DataAnalysis #DataExploration #Unmixing #NMF #Python #JuliaLang #RStats

  8. RE: floss.social/@rdnielsen/116365

    The third and last of the series on unmixing using NMF is now posted at

    dblog.vitumbre.tech/dart/unmix

    Part 3 illustrates the variability of results that can occur when repeatedly unmixing the same data set, and presents approaches to addressing the resultant uncertainty.

    #DataAnalysis #DataExploration #Unmixing #NMF #Python #JuliaLang #RStats

  9. RE: floss.social/@rdnielsen/116365

    The third and last of the series on unmixing using NMF is now posted at

    dblog.vitumbre.tech/dart/unmix

    Part 3 illustrates the variability of results that can occur when repeatedly unmixing the same data set, and presents approaches to addressing the resultant uncertainty.

    #DataAnalysis #DataExploration #Unmixing #NMF #Python #JuliaLang #RStats

  10. RE: floss.social/@rdnielsen/116365

    The third and last of the series on unmixing using NMF is now posted at

    dblog.vitumbre.tech/dart/unmix

    Part 3 illustrates the variability of results that can occur when repeatedly unmixing the same data set, and presents approaches to addressing the resultant uncertainty.

    #DataAnalysis #DataExploration #Unmixing #NMF #Python #JuliaLang #RStats

  11. RE: floss.social/@rdnielsen/116363

    Part 2 of this series on unmixing is now available:

    dblog.vitumbre.tech/dart/unmix

    Part 2 addresses the challenge of deciding how many end members are in a data set, recommends algorithms for Python, Julia, and R, and illustrates how several factors affect that determination.

    #DataAnalysis #DataExploration #Unmixing #NMF #Python #JuliaLang #RStats

  12. RE: floss.social/@rdnielsen/116363

    Part 2 of this series on unmixing is now available:

    dblog.vitumbre.tech/dart/unmix

    Part 2 addresses the challenge of deciding how many end members are in a data set, recommends algorithms for Python, Julia, and R, and illustrates how several factors affect that determination.

    #DataAnalysis #DataExploration #Unmixing #NMF #Python #JuliaLang #RStats

  13. RE: floss.social/@rdnielsen/116363

    Part 2 of this series on unmixing is now available:

    dblog.vitumbre.tech/dart/unmix

    Part 2 addresses the challenge of deciding how many end members are in a data set, recommends algorithms for Python, Julia, and R, and illustrates how several factors affect that determination.

    #DataAnalysis #DataExploration #Unmixing #NMF #Python #JuliaLang #RStats

  14. RE: floss.social/@rdnielsen/116363

    Part 2 of this series on unmixing is now available:

    dblog.vitumbre.tech/dart/unmix

    Part 2 addresses the challenge of deciding how many end members are in a data set, recommends algorithms for Python, Julia, and R, and illustrates how several factors affect that determination.

    #DataAnalysis #DataExploration #Unmixing #NMF #Python #JuliaLang #RStats

  15. RE: floss.social/@rdnielsen/116363

    Part 2 of this series on unmixing is now available:

    dblog.vitumbre.tech/dart/unmix

    Part 2 addresses the challenge of deciding how many end members are in a data set, recommends algorithms for Python, Julia, and R, and illustrates how several factors affect that determination.

    #DataAnalysis #DataExploration #Unmixing #NMF #Python #JuliaLang #RStats

  16. I just posted part 1 of a 3-part series on unmixing of data sets using non-negative matrix factorization.

    dblog.vitumbre.tech/dart/unmix

    Part 1 contains implementations in Python, Julia, and R, and includes an assessment of the relative accuracy of these implementations.

    Parts 2 and 3 will follow shortly, and will contain more detail on the identification of, and accurate characterization of, unmixing end members.

    #DataAnalysis #DataExploration #Python #JuliaLang #RStats #Unmixing #NMF

  17. I just posted part 1 of a 3-part series on unmixing of data sets using non-negative matrix factorization.

    dblog.vitumbre.tech/dart/unmix

    Part 1 contains implementations in Python, Julia, and R, and includes an assessment of the relative accuracy of these implementations.

    Parts 2 and 3 will follow shortly, and will contain more detail on the identification of, and accurate characterization of, unmixing end members.

    #DataAnalysis #DataExploration #Python #JuliaLang #RStats #Unmixing #NMF

  18. I just posted part 1 of a 3-part series on unmixing of data sets using non-negative matrix factorization.

    dblog.vitumbre.tech/dart/unmix

    Part 1 contains implementations in Python, Julia, and R, and includes an assessment of the relative accuracy of these implementations.

    Parts 2 and 3 will follow shortly, and will contain more detail on the identification of, and accurate characterization of, unmixing end members.

    #DataAnalysis #DataExploration #Python #JuliaLang #RStats #Unmixing #NMF

  19. I just posted part 1 of a 3-part series on unmixing of data sets using non-negative matrix factorization.

    dblog.vitumbre.tech/dart/unmix

    Part 1 contains implementations in Python, Julia, and R, and includes an assessment of the relative accuracy of these implementations.

    Parts 2 and 3 will follow shortly, and will contain more detail on the identification of, and accurate characterization of, unmixing end members.

    #DataAnalysis #DataExploration #Python #JuliaLang #RStats #Unmixing #NMF

  20. I just posted part 1 of a 3-part series on unmixing of data sets using non-negative matrix factorization.

    dblog.vitumbre.tech/dart/unmix

    Part 1 contains implementations in Python, Julia, and R, and includes an assessment of the relative accuracy of these implementations.

    Parts 2 and 3 will follow shortly, and will contain more detail on the identification of, and accurate characterization of, unmixing end members.

    #DataAnalysis #DataExploration #Python #JuliaLang #RStats #Unmixing #NMF