majority voting classifier
[məˈdʒɒrɪti ˈvoʊtɪŋ ˈklæsɪfaɪər]
nounpl: majority voting classifiers
classificador por votação por maioria
1. An ensemble machine learning method that combines multiple classifiers and makes predictions by taking the class that receives the most votes from individual classifiers
The majority voting classifier combined three different neural networks to improve prediction accuracy.
O classificador por votação por maioria combinou três redes neurais diferentes para melhorar a precisão da previsão.
2. A voting strategy in machine learning where each base classifier casts one vote and the class with the most votes is selected as the final prediction
In this ensemble approach, a majority voting classifier uses hard voting to make final decisions.
Nesta abordagem de ensemble, um classificador por votação por maioria usa votação dura para tomar decisões finais.
This is a specialized technical term primarily used in machine learning, data science, and artificial intelligence contexts. It is used identically in both American English and Brazilian Portuguese technical communities, though slight variations exist between Brazilian and European Portuguese conventions. The term reflects the democratic principle of majority decision-making applied to algorithmic ensemble methods.
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