Lasso Regression with Scikit-Learn (Beginner Friendly)

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  • Опубликовано: 12 дек 2024

Комментарии • 15

  • @RyanAndMattDataScience
    @RyanAndMattDataScience  4 месяца назад

    Hey guys I hope you enjoyed the video! If you did please subscribe to the channel!
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  • @RyanAndMattDataScience
    @RyanAndMattDataScience  Год назад +5

    I made a mistake within this video: fit_transform must be only on train set, for test there must be only transform.

    • @akhileshpawar7163
      @akhileshpawar7163 23 дня назад

      if you did this mistake why did it not overfit i.e. why the error was not zero?

  • @ryuhayabusa3540
    @ryuhayabusa3540 Год назад

    Just found your channel, loving the python tutorials

  • @HenriqueSantos-xd1eg
    @HenriqueSantos-xd1eg 4 месяца назад

    have you tried pycaret?

  • @SusanElliott-w5q
    @SusanElliott-w5q 2 месяца назад

    so what if the lasso drop two features who can you tell which features it dropeed when you zip teh freatures and coeef back together???

  • @misterx3321
    @misterx3321 Год назад

    Nice video! Say does LASO-Regression only apply to multiple linear regression where you have multiple variables that contribute to the target variable?

    • @RyanAndMattDataScience
      @RyanAndMattDataScience  Год назад

      no, it can be applied to other linear regressions although multiple is probably most common

  • @736939
    @736939 Год назад

    Dear Ryan, could you please write all these codes with pipelines and columns transformers, it would be great to see the best practice with all sklearn pipeline tools. Thank you for this great work, and more feature engineering please :)

    • @RyanAndMattDataScience
      @RyanAndMattDataScience  Год назад

      Hey, have a pipeline and transformer videos. + working on a Kaggle project with them.
      I’ll also be using pipelines with the voting regressor + stacking vids.
      For the simple model vids, going to focus on background of model, basic example, and tuning

  • @lockelancer8193
    @lockelancer8193 9 месяцев назад

    Very useful video, very cool. Saved me a bunch of time and effort from trying to learn it R A W.