What is Overfitting in Machine Learning?

overfitting Model overfitting is a statistical error in supervised ML, whereby the trained model fits the noise in the training data rather than its actual pattern

Overfitting occurs when a machine learning model matches the training data too closely, losing its ability to classify and predict new data An overfit model overfitting Abstract Overfitting is a fundamental issue in supervised machine learning which prevents us from perfectly generalizing the models to well fit observed data