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NCA-ADS - Data Manipulation and Preparation - Section 1.5

Handle class imbalance.

Describe techniques for addressing class imbalance, including oversampling, undersampling, and class-weight adjustment. Choose the most appropriate strategy given the dataset size, the cost of false positives versus false negatives, and the chosen classifier.

More in this domain

Integrate, join, and manipulate data using cuDF and pandas.Section 1.1
Handle data cleaning and data quality.Section 1.2
Build GPU-accelerated ETL workflows.Section 1.3
Apply feature engineering.Section 1.4
Apply dimensionality reduction.Section 1.6
Use Parquet storage for data.Section 1.7

Back to all Data Manipulation and Preparation objectives, or the NCA-ADS cert hub.

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