Method of machine learning
Also known as incremental machine learning
5 statements · 20% with external sources · numbers in brackets are citations
3 identifiers linking incremental learning across the web's reference databases
From Wikipedia, the free encyclopedia · Read full article · Text CC BY-SA 4.0
In computer science, incremental learning is a method of machine learning in which input data is continuously used to extend the existing model's knowledge i.e. to further train the model. It represents a dynamic technique of supervised learning and unsupervised learning that can be applied when training data becomes available gradually over time or its size is out of system memory limits. Algorithms that can facilitate incremental learning are known as incremental machine learning algorithms. In contemporary machine learning literature, settings that require learning from a sequence of tasks while limiting catastrophic forgetting are often discussed under the closely related term continual learning.