Overfitting 편집하기 (부분)

==Signs of Overfitting==
There are several indicators that a model might be overfitting:
*'''High Training Accuracy, Low Test Accuracy''': The model performs very well on training data but poorly on test or validation data.
*'''Complex Decision Boundaries''': For models like decision trees, overly complex boundaries or deep trees are signs that the model has learned specific details instead of general patterns.
*'''Inconsistent Predictions on Similar Data''': Overfit models may produce erratic predictions when encountering slight variations in the data.