parametric learning
[/ˌpærəˈmɛtrɪk ˈlɜrnɪŋ/]
noun
aprendizado paramétrico
1. A machine learning approach where the model assumes a fixed functional form with a finite number of parameters that are learned from data
Parametric learning methods like linear regression assume a specific relationship between input and output variables.
Métodos de aprendizado paramétrico como regressão linear assumem uma relação específica entre variáveis de entrada e saída.
2. In neural networks and statistics, the process of training models by estimating fixed parameters based on training data
The neural network uses parametric learning to optimize its weights and biases during training.
A rede neural usa aprendizado paramétrico para otimizar seus pesos e vieses durante o treinamento.
3. A learning paradigm that contrasts with non-parametric methods by making explicit assumptions about data distribution
Parametric learning is more efficient than non-parametric learning when the model assumptions are correct.
O aprendizado paramétrico é mais eficiente que o aprendizado não-paramétrico quando as suposições do modelo estão corretas.
This is a technical term primarily used in computer science, artificial intelligence, and statistics education and research. It is equally understood in both Brazil and Portugal in academic circles, though Brazilian Portuguese typically uses 'aprendizado' while European Portuguese uses 'aprendizagem'. In international tech companies operating in Brazil, the English term 'parametric learning' is commonly used alongside the Portuguese translation.
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