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In this tutorial, we delve into the powerful world of ensemble techniques, focusing on BalancedRandomForest to achieve data balance in machine learning models.
🔍 Key Highlights:
Learn the fundamentals of BalancedRandomForest for handling imbalanced datasets.
Walkthrough a step-by-step implementation using Python and scikit-learn.
Explore the impact on model performance through real-world examples and metrics.
👩💻 Resources - Data, Code and Tools Used:
Data used in balancing work - github.com/LEA...
Data Balancing & Model Building - github.com/LEA...
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