Improving prediction accuracy| Outlier analysis in python| Multicollinearity in regression

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  • Опубліковано 28 січ 2025

КОМЕНТАРІ • 11

  • @03Jasie
    @03Jasie Рік тому

    Hi, is part three coming soon?!

    • @03Jasie
      @03Jasie Рік тому

      Your videos are so informative and easy to follow. Thank you for all your help!

  • @sophiayacob9823
    @sophiayacob9823 3 роки тому

    Hi, Is it okay to remove outliers in a timeseries dataset. Because removing any values would affect the continuity of the dataset.

  • @kashyapjyotigohain4905
    @kashyapjyotigohain4905 3 роки тому

    Thanks for the session brother 🙏

  • @ishanayus2979
    @ishanayus2979 3 роки тому

    Bro could you please publish the next video how to reduce errors

  • @ireneanibogwu7242
    @ireneanibogwu7242 4 роки тому

    Hi, thanks for your video. I was under the impression that x variables a highly multi-colinear if the have higher values leading closer to 1 on a heat map. How can diesel and petroleum have multicollinearity in this case when they have the lowest values? Just trying to understand better

    • @ireneanibogwu7242
      @ireneanibogwu7242 4 роки тому +1

      never mind I understand now. The reason they are co-linear is that as one value increases, the other decreases.. so with -0.98 score, it's saying as value of petrol increases, the value of diesel decreases since a linear relationship can both be positive or negative. Thanks!

    • @ponshankarpalanivel
      @ponshankarpalanivel  4 роки тому +1

      @@ireneanibogwu7242 Hi, Thank you very much for watching my video. That's exactly it. I am glad you got it. All the best !!

  • @ishanayus2979
    @ishanayus2979 3 роки тому

    If possible please teach UNet based on any examples (practical)

  • @prasaddeshpande8605
    @prasaddeshpande8605 3 роки тому

    Correlation value take values between -1 and 1.