Technical
Underfitting
Definition
When a machine learning model is too simple to capture the underlying patterns in the data, resulting in poor performance on both training and test data.In-Depth Explanation
Underfitting happens when the model lacks the capacity to learn from the data. It fails to capture important relationships and makes overly simplistic predictions. Signs include poor accuracy on both training and test sets. Solutions include using more complex models, adding features, reducing regularization, or training longer.
Real-World Example
Trying to fit a straight line to data that clearly follows a curved pattern, resulting in poor predictions everywhere.
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