How to Identify Overfitting Machine Learning Models in Scikit-Learn
Last Updated on November 27, 2020
Overfitting is a common explanation for the poor performance of a predictive model.
An analysis of learning dynamics can help to identify whether a model has overfit the training dataset and may suggest an alternate configuration to use that could result in better predictive performance.
Performing an analysis of learning dynamics is straightforward for algorithms that learn incrementally, like neural networks, but it is less clear how we might perform the same analysis with other algorithms that do not learn incrementally, such as decision trees, k-nearest neighbors, and other general algorithms in the scikit-learn machine learning library.
In this tutorial, you will discover how to identify overfitting for machine learning models in