Correlation Matrix (Numerical) | Feature Selection | Python

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  • Опубликовано: 22 авг 2024

Комментарии • 9

  • @sweetyrani6727
    @sweetyrani6727 Год назад +2

    could you please explain how dimension reduction done using best first search with an example of correlation matrix .

  • @maryamshahzadi3364
    @maryamshahzadi3364 Год назад +2

    this video helped me thanks

  • @tinytrip6844
    @tinytrip6844 7 месяцев назад +1

    hi aswin bro, values more than 0.05? or more than 0.5 corr dependies with each other? @9.05 sec

    • @HackersRealm
      @HackersRealm  7 месяцев назад

      it depends on the range, if it's closer to 1, it's highly correlated,, if it's in middle like 0.5, there is medium correlation, etc.,

  • @tinytrip6844
    @tinytrip6844 7 месяцев назад

    HI Aswin bro, what does it meant the term you used "its leaking the data" @4.48 sec.

  • @karthikrajendran3394
    @karthikrajendran3394 Год назад

    What should we do with -ve correlated columns?

    • @HackersRealm
      @HackersRealm  Год назад

      positive and negative both are to be considered which is at extremes.

  • @vijaynath1986
    @vijaynath1986 8 месяцев назад

    Hi, Video did not clearly say, which column to drop and which one to keep. No conclusion. More info could be better