Incremental decision tree

Tree (set theory)

Algorithm

Machine learning

Data mining

Search algorithm

Mathematical analysis

Limit (mathematics)

Artificial intelligence

Tree structure

ID3 algorithm

Binary tree

Search tree

Mathematics

Computer science

State (computer science)

Decision tree learning

Decision tree model

Theoretical computer science

Decision tree

Interval tree

We introduce a novel incremental decision tree learning algorithm, Hoeffding Anytime Tree, that is statistically more efficient than the current state-of-the-art, Hoeffding Tree. We demonstrate that an implementation of Hoeffding Anytime Tree---"Extremely Fast Decision Tree'', a minor modification to the MOA implementation of Hoeffding Tree---obtains significantly superior prequential accuracy on most of the largest classification datasets from the UCI repository. Hoeffding Anytime Tree produces the asymptotic batch tree in the limit, is naturally resilient to concept drift, and can be used as a higher accuracy replacement for Hoeffding Tree in most scenarios, at a small additional computational cost.

Extremely Fast Decision Tree