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Feature selection in machine learning | Full course

2023-03-25 Science & Technology
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Description

Full source code on GitHub: https://github.com/marcopeix/youtube_tutorials/blob/main/YT_01_feature_selection.ipynb Introduction - 0:00 Initial code setup - 2:19 Variance threshold - 11:04 Variance threshold (code) - 13:02 Filter method - 19:39 Filter method (code) - 21:27 RFE - 29:08 RFE (code) - 30:42 Boruta - 37:12 Boruta (code) - 41:21 Thank you - 46:35 A full course on feature selection in machine learning projects. We first cover a naive method based on variance. Then we move on to filter method and wrapper method like recursive feature elimination or RFE. Finally, implement the Boruta algorithm.

Top Comments (10)

@ax5344 2024-06-13

I like the logic of this video. You showed the baseline, then three additional methods, then compare them in the end. Thanks a lot for sharing the technique. The feature/target matrix is also very helpful. My question is the principle or concept behind the filter method, RFE, and boruta. Is it possible to do a video on them?

6
@samuelliaw951 2023-11-20

Really great content! Learnt a lot. Thanks for your hard work!

2
@tanyaalexander1460 2024-04-20

I am a noob to data science and feature selection. Yours is the most succinct and clear lesson I have found... Thank you!

2
@mauroSfigueira 2024-05-25

Hugely informative and educational content. Many feature engineering videos are not that instructive.

1
@ildestino6200 2025-02-04

You’re brilliant that’s the first time I hear such clear and comprehensive explanation of feat selection. Thank you very very much and keep up the amazing work ❤

1
@lc-rezende 2026-01-28

Thank you for the video!

0
@ednaldogomes6124 2024-10-11

Congratulations and thanks for the excellent tutorial. You gained another subscriber👏👏👏

0
@pedro_tonom 2024-07-18

Amazing video and excelent didatic. Congrats for the great quality, helped me a lot!

0
@NulliusInVerba8 2024-08-03

This is extremely helpful and informative. Thanks a LOT!

0
@maxmg5660 2025-12-16

Really enjoyed the tutorial, thank you🙏

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