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GitHub / hanfei1986 / Comparison-between-RandomForestClassifier-and-BalancedRandomForestClassifier

Imbalanced data commonly exist in real world, especially in anamoly-detection tasks. Handling imbalanced data is important to the tasks, otherwise the predictions are biased towards the majority class. BalancedRandomForestClassifier can deal with the imbalanced data without knowing any novel techniques like SMOTE.

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PURL: pkg:github/hanfei1986/Comparison-between-RandomForestClassifier-and-BalancedRandomForestClassifier

Stars: 0
Forks: 0
Open issues: 0

License: None
Language: Jupyter Notebook
Size: 5.37 MB
Dependencies parsed at: Pending

Created at: almost 2 years ago
Updated at: almost 2 years ago
Pushed at: almost 2 years ago
Last synced at: almost 2 years ago

Topics: balanced-random-forest-classifier, imbalanced-data, random-forest-classifier

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