Uploaded June 2023 | Updated September 2026, 2 days ago

---

In this video, we dive into the world of filtered-based feature selection techniques for machine learning models. If you're looking to improve your model's performance and avoid issues like overfitting or underfitting, selecting the right columns and data is crucial. Today, we focus on filtered-based approaches, where we evaluate the value and correlation of each feature within the dataset. We explore four techniques: information gain, chi-squared test, Fisher's score, and missing value ratio. Join us to learn how these techniques can help you identify the most impactful features for your machine learning model. Stay tuned for future videos where we'll cover other feature selection approaches.

Here's the full article for both supervised and unsupervised feature selection techniques, including filter-based, wrapper-based, and embedded approaches: stratascratch.com/blog/feature-selection-techniques-in-machine-learning/?utm_source=youtube&utm_medium=click&utm_campaign=YT+feature+selection+techniques

______________________________________________________________________

👉 Subscribe to my channel: bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: bit.ly/3jifw81
👉 Playlist for data science interview tips: bit.ly/2G5hNoJ
👉 Playlist for data science projects: bit.ly/StrataScratchProjectsYouTube
👉 Practice more real data science interview questions: platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+feature+selection+techniques

______________________________________________________________________

Timeline:

Feature Selection Techniques Overview: (0:00​​​)
What is supervised learning: (0:51)
Information Gain: (1:37)
Chi-square Test: (2:31)
Fisher's Score: (3:08)
Missing Value Ration: (3:41)
Conclusion: (4:22​​)

______________________________________________________________________

About The Platform:

StrataScratch (platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+feature+selection+techniques) is a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and Python), statistics, probability, product sense, and business cases.

So, if you want more interview practice with real data science interview questions, visit platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+feature+selection+techniques. All questions are free and you can even execute SQL and Python code in the IDE. Still, if you want to check out the solutions from other users or from the StrataScratch team, you can use ss15 for a 15% discount on the premium plans.


______________________________________________________________________

Contact:

If you have any questions, comments, or feedback, please leave them here!
Feel free to also email us at team@stratascratch.com

______________________________________________________________________
#featureselection #machinelearning #datascience #supervisedlearning #chisquaretest #machinelearningalgorithm #machinelearningwithpython #datascienceskills #python