An Overview of Overfitting and its Solutions

Overfitting is a fundamental issue in supervised machine learning which prevents us from perfectly generalizing the models to well fit observed data on training

Regularization is the most popular technique to prevent overfitting It is a group of methods that forces the learning algorithms to make a model simpler

overfitting One way to manage overfitting and underfitting is to use statistical validation methods, such as cross-validation and regularization Cross-

overfitting To recap, overfitting occurs when the model has a high correlation with the training data, resulting in models that are very accurate on the