Glossary term
Glossary term
Foundations
A collection of models trained independently whose predictions are averaged or aggregated. In many cases, an ensemble produces better predictions than a single model. For example, a random forest is an ensemble built from multiple decision trees. Note that not all decision forests are ensembles.
See Random Forest in Machine Learning Crash Course for more information.
Created for this library
A retail demand team uses an ensemble of a gradient-boosted tree and a neural model to combine the strengths of each on tabular and learned features.
A credit risk team uses an ensemble of two scorecards trained on different vintages to stabilize predictions during macroeconomic shifts.
A search ranking team uses an ensemble of a feature-engineered model and a deep ranker to improve quality on long-tail queries.
Definition source: Google for Developers Machine Learning Glossary | Creative Commons Attribution 4.0 License