Description
Imagine a fruit ripening on a tree. If you leave it too long, it becomes overripe and spoils. Similarly, training a model for too long in AI can lead to overfitting, where it performs well on the training data but poorly on new, unseen data. Early stopping acts like a time machine, allowing you to peek into the future of your model’s performance and stop training at its peak, preventing it from spoiling.
Here is an overview of the concept and implementation of early stopping, a crucial technique for preventing overfitting in AI models. Plus, how it works, the key parameters involved, and best practices for effectively applying it in your model training process. Get ready to master the art of stopping at the right time and unlock your model’s true potential.
Kognition.Info paid subscribers can download this and many other How-To guides. For a list of all the How-To guides, please visit https://www.kognition.info/product-category/how-to-guides/