Clustering with R (FactoMineR & Factoshiny)

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  • เผยแพร่เมื่อ 1 ธ.ค. 2024

ความคิดเห็น • 9

  • @djaleleddinegherissi5084
    @djaleleddinegherissi5084 6 หลายเดือนก่อน +1

    After the MCA or PCA followed by HCA, how to identify the number of individuals in each cluster and their ID ? Sometimes they are superposed and we can't distinguish them in graphs. Thank you in advance

  • @borbro9077
    @borbro9077 4 ปีที่แล้ว

    Many thanks for all your videos very interesting.

  • @hansdadther2971
    @hansdadther2971 3 ปีที่แล้ว

    MUCHAS GRACIAS ME AYUDO MUCHO¡¡¡ thanks a lot¡¡, merci beaucoup pour votre vidéo et tous les explications.¡¡¡¡¡

  • @georgelevasser2778
    @georgelevasser2778 4 ปีที่แล้ว

    thanks guys! This is all very very helpful

  • @ramseslandaverde1378
    @ramseslandaverde1378 3 ปีที่แล้ว

    Hi Guys, is there in Factoshiny any useful tool/option to measure the quality of precision of the clustering?

  • @ramseslandaverde1378
    @ramseslandaverde1378 3 ปีที่แล้ว

    Wow this is a great r package, thank you so much for sharing this valuable knowledge. Kind regards! I realize that there is not a library as Factoshiny... :-(
    > library(Factoshiny)
    Error in library(Factoshiny) : there is no package called ‘Factoshiny’

    • @faiqahfudzi8388
      @faiqahfudzi8388 3 ปีที่แล้ว

      Yes Sir, same happen to me. Do you find out the solution? Cus I am still trying figure out how to analyse my data using PCA in R

    • @ramseslandaverde1378
      @ramseslandaverde1378 3 ปีที่แล้ว

      @@faiqahfudzi8388 yes I installed it from packages , Factoshiny works into FactoMineR package.
      > library(FactoMineR)
      > library(Factoshiny)

    • @diegodavila6186
      @diegodavila6186 2 ปีที่แล้ว

      @@faiqahfudzi8388 Hello!! That error message commonly adresses a situation in which there has been no prior installation of the package in your computer. Try running this:
      #Install package
      install.packages("Factoshiny")
      #Let it run
      #Now call package to the R session
      library(Factoshiny)
      Kind regards