imbalanced data

How Does Imbalanced Data Affect Model Performance?

Imbalanced data can lead to several issues in model performance:
- Bias Towards Majority Class: Models may predict the majority class more often, leading to a high number of false negatives.
- Misleading Accuracy: High overall accuracy might be misleading if the model is predominantly predicting the majority class correctly while failing to predict the minority class.
- Poor Generalization: Models trained on imbalanced data may not generalize well to new, unseen data, especially for the minority class.

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