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What is Simplifying Neural Network Training about?

Class imbalance in machine learning and image processing occurs when one class has significantly more examples than another, leading to biased model performance and misleading evaluation metrics. Techniques to address this issue include data augmentation, transfer learning, cost-sensitive learning, and various sampling methods. Additionally, optimizing hyperparameters such as learning rate, batch size, and network architecture is crucial for improving model performance.

Author

sumukhagouri

Language

EN