What is an ensemble?
A collection of models trained independently whose predictions are averaged or aggregated.
ensemble explained in plain English
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.
Example
Practitioners refer to ensemble when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.
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The number of correct classification predictions divided by the total number of predictions.
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A function that enables neural networks to learn nonlinear (complex) relationships between features and the label.
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A training approach in which the algorithm chooses some of the data it learns from.
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Synonym for tuning or fine-tuning.
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See hierarchical clustering.
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The process of identifying outliers.
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See PR AUC (Area under the PR Curve).
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See AUC (Area under the ROC curve).