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YouTube

Classification Trees in Python from Start to Finish

StatQuest with Josh Starmer via YouTube

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Overview

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This course demonstrates an end-to-end Python workflow for building a scikit-learn classification tree that predicts heart disease from continuous and categorical patient data. It covers missing-data handling, one-hot encoding, cost-complexity pruning, and interpretation of the final tree.

Syllabus

This webinar was recorded 20200528 at am New York time.
Awesome song and introduction
Import Modules
Import Data
Missing Data Part 1: Identifying
Missing Data Part 2: Dealing with it
Format Data Part 1: X and y
Format Data Part 2: One-Hot Encoding
Build Preliminary Tree
Pruning Part 1: Visualize Alpha
Pruning Part 2: Cross Validation
Build and Draw Final Tree

Taught by

StatQuest with Josh Starmer

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