Pandas
Machine Learning
When a model learns noise in data reducing its generalization.
Detailed Explanation
Overfitting occurs when a machine learning model learns not only the underlying patterns but also the noise or random fluctuations in the training data. This causes the model to perform exceptionally well on training data but poorly on new, unseen data, as it fails to generalize effectively. Techniques like cross-validation, regularization, and pruning help prevent overfitting.
Use Cases
- •Use case: Enhancing model validation techniques to prevent overfitting and improve accuracy on unseen test datasets.
Related Terms
Other terms in the Machine Learning category