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When data classes are not equal, use professional methods to handle imbalanced sources. Explore resampling, cost-sensitive learning, and performance metrics that go beyond simple accuracy. This technical walkthrough provides the clarity needed to build stable models and report their success with the highest level of academic integrity.
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