ensemble classifier
[ɛnˈsɑːmbəl ˈklæsɪfaɪər]
nounpl: ensemble classifiers
classificador em conjunto
1. A machine learning model that combines multiple base classifiers to make predictions, typically achieving better performance than any individual classifier alone
The ensemble classifier used random forests and gradient boosting to improve accuracy on the dataset.
O classificador em conjunto usou florestas aleatórias e reforço de gradiente para melhorar a precisão no conjunto de dados.
2. A meta-algorithm that trains multiple learners and aggregates their predictions through voting, averaging, or other combination strategies
An ensemble classifier combining decision trees outperformed the individual models.
Um classificador em conjunto combinando árvores de decisão superou os modelos individuais.
This is primarily a technical term used in machine learning and artificial intelligence fields. It is commonly used by Brazilian tech professionals, data scientists, and academics with minimal regional variation. The term is universally recognized in international machine learning communities, and English terminology is often retained even in Portuguese-language contexts. In Brazil, tech professionals may use 'classificador em conjunto' or sometimes retain the English 'ensemble classifier' in technical documentation and discussions.
Related Idioms & Phrases
strength in numbers - referring to combining multiple classifiers for better results
two heads are better than one - conceptual parallel to ensemble methods
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