-1
$\begingroup$

I've recently started using Kaggle, and I've noticed that for a lot of these jupyter notebooks written by others, when they use Ridge/Lasso, they don't standardize the non-categorical numerical features. My understanding is it's best practice to standardize when regularizing, so there's some form of parity when it comes to penalizing the different coefficients.

Why is there (seemingly) a lack of this standardization practice on Kaggle? Am I missing something here?

Here are a couple examples: https://www.kaggle.com/mohaiminul101/car-price-prediction

https://www.kaggle.com/burhanykiyakoglu/predicting-house-prices/comments

Honestly. I feel like the majority that I've seen that use Lasso/Ridge do not do any standardization, and I usually only look at the highest voted ones for pretty popular datasets, so I'm a little surprised.

Improve this question
$\endgroup$
6
  • 1
    $\begingroup$ Could you please share a specific Notebook $\endgroup$
    – 10xAI
    Commented May 4, 2021 at 16:23
  • $\begingroup$ @10xAI I just included one. I'll update the OP with I find more, but I didn't make a list when I was going through codes before. But honestly, I'm pretty sure at least 75% of the ones that I looked at (I only looked at the most highly voted ones too) did not do any standardization when using Lasso/Ridge $\endgroup$
    – student010101
    Commented May 5, 2021 at 0:02
  • $\begingroup$ I don't think this question is worth to be responded on SE, It is more suitable for a discussion forum on Kaggle since this is a 100% focuses on what is being done there, and not in what is theoretically correct $\endgroup$
    – Multivac
    Commented May 9, 2021 at 14:43
  • 1
    $\begingroup$ @JulioJesus I disagree. SE isn't only for "theoretical" discussions. There's plenty of stuff on here about what is done in practice $\endgroup$
    – student010101
    Commented May 9, 2021 at 15:03
  • 1
    $\begingroup$ ...especially in such an applied field as DS... $\endgroup$
    – student010101
    Commented May 9, 2021 at 15:10

1 Answer 1

Reset to default
1
$\begingroup$

Kaggle is a crowd source platform with no quality control. It is to be expected that there will be deviations from best practices.

Improve this answer
$\endgroup$
3
  • $\begingroup$ Yeah I understand, but I've only looked at the top rated posts for pretty popular datasets, so it's a bit surprising. Do you have any suggestions on other sources that I can look at that have best practices? $\endgroup$
    – student010101
    Commented May 5, 2021 at 0:05
  • $\begingroup$ Textbooks and package documentation are often higher quality than crowd sourced websites. One reason is they both have many people reviewing them. $\endgroup$
    – Brian Spiering
    Commented May 5, 2021 at 11:23
  • $\begingroup$ Do you have any recommended textbooks for dataset analysis examples? I'm particularly interested in regression analyses. The one book that I have is "Hands on Machine Learning with Scikit-Learn, Keras & Tensorflow," but there was only one example on regression, IIRC, on the california housing dataset. $\endgroup$
    – student010101
    Commented May 5, 2021 at 13:59

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.