What are some examples of overfitting in machine learning?

What are some examples of overfitting in machine learning?

Overfitting occurs when a model learns the training data too well, capturing noise instead of the underlying pattern. For example, a decision tree that perfectly classifies training data but performs poorly on unseen data is overfitting.

Can you give me a specific scenario where this happens?

Sure! Imagine a model trained to recognize cats in images. If it learns to identify specific features like the background or lighting of the training images instead of general cat features, it may fail to recognize cats in different settings.

How can we prevent overfitting?

Common techniques include using cross-validation, pruning decision trees, and applying regularization methods to simplify the model.

What is regularization?

Regularization is a technique used to prevent overfitting by adding a penalty for larger coefficients in the model, encouraging simpler models.