Machine Learning: Random Forest with Python from Scratch - Feature Importance

Machine Learning: Random Forest with Python from Scratch - Feature Importance

Assessment

Interactive Video

Computers

9th - 10th Grade

Hard

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The video tutorial explains how to determine the importance of features in a dataset using a trained model, specifically a random forest classifier. It covers the process of calculating feature importance, debugging common errors, and interpreting the results. The tutorial also hints at future lessons where the instructor will teach how to implement these functions from scratch without relying on built-in libraries like SK Learn.

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2 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What steps did the teacher take to correct the error in the code?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

What will the teacher focus on in the next videos regarding model implementation?

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