AnswerQuestion: In the context of machine learning, what is "overfitting"?

Tue, 05 May 2026 05:23:38 +0000

## What Is Overfitting in Machine Learning? Understanding the Key Challenge and How to Avoid It In the world of machine learning, achieving high predictive accuracy is the ultimate goal. However, data scientists often face a major obstacle: overfitting. But what exactly is overfitting, and why does it matter so much in model development? ### Overfitting Defined: When Models Learn Too Much Overfitting occurs when a machine learning model learns the training data too well—to the point that it memorizes noise, random fluctuations, and even outliers rather than capturing the underlying patterns. As a result, the model performs exceptionally on training data but fails to generalize to new, unseen data. This leads to poor performance in real-world applications, where the model must make predictions on novel samples.