Principal Component Analysis Explained

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  • Опубликовано: 27 окт 2024

Комментарии • 9

  • @marksanda9786
    @marksanda9786 7 месяцев назад +3

    The best explanation of PCA that I have ever heard, hands down.

  • @suhasjadhav1610
    @suhasjadhav1610 2 года назад +7

    It is one of the most intuitive and crystal clear explanation of PCA concept in less than 10 minutes.

  • @j.larrycampbell8195
    @j.larrycampbell8195 Год назад +1

    Thank you very much, @RayBiotech, for providing this excellent description of PCA!

  • @anonymousentity5106
    @anonymousentity5106 Год назад +3

    Thanks! This is amazing!

  • @ranjanpal7217
    @ranjanpal7217 11 месяцев назад

    Amazing explanation

  • @leolei9352
    @leolei9352 2 года назад +2

    Thanks for clear explanation

  • @tafarabute1483
    @tafarabute1483 2 года назад +1

    Good explanation

  • @chicanicajfcp
    @chicanicajfcp 11 месяцев назад

    Wrong! The maximum number of PC's are min(n-1, k). In the example you had 10 samples and 40 attributes. The answer should be

    • @RayBiotech
      @RayBiotech  11 месяцев назад

      Thanks for the comment! Yes the last PC will be trivial or nearly 0 when n