supervised learning models
[/ˈsuːpərvɪzd ˈlɜːrnɪŋ ˈmɒdəlz/]
nounpl: supervised learning models
modelos de aprendizado supervisionado
1. Machine learning algorithms trained on labeled datasets where each input has a corresponding correct output, used to make predictions or classifications on new, unseen data
Supervised learning models require a training dataset with labeled examples to learn the relationship between inputs and outputs.
Modelos de aprendizado supervisionado requerem um conjunto de dados de treinamento com exemplos rotulados para aprender a relação entre entradas e saídas.
2. Algorithms that learn from historical data containing known answers to predict future outcomes or classify new instances
Common supervised learning models include linear regression, decision trees, and neural networks.
Modelos comuns de aprendizado supervisionado incluem regressão linear, árvores de decisão e redes neurais.
This term is part of the globalized tech and AI vocabulary, used consistently across English and Portuguese-speaking countries. In Brazil, the tech industry increasingly adopts this terminology in English, though Portuguese translations are standard in academic settings. In Portugal, European Portuguese conventions apply with slightly different terminology.
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