feature separation
[/ˈfiːtʃər ˌsɛpəˈreɪʃən/]
nounpl: feature separations
separação de características
1. In machine learning and data science, the process of isolating or distinguishing individual features or attributes from a dataset or model to analyze their individual contributions or effects
Feature separation techniques help identify which variables have the most impact on model predictions.
As técnicas de separação de características ajudam a identificar quais variáveis têm o maior impacto nas previsões do modelo.
2. In signal processing or computer vision, the decomposition or isolation of distinct signal components or visual elements from a mixed or complex input
Feature separation in audio processing allows us to isolate vocals from background music.
A separação de características no processamento de áudio nos permite isolar vocais da música de fundo.
3. In linguistics or natural language processing, the extraction of distinct linguistic or semantic features from text or speech
Feature separation in NLP helps distinguish between parts of speech and syntactic elements.
A separação de características em PNL ajuda a distinguir entre partes do discurso e elementos sintáticos.
This is primarily a technical term used in the fields of machine learning, data science, signal processing, and artificial intelligence. It is equally used in both Brazilian and Portuguese technical communities, as well as in international tech hubs like São Paulo and Lisbon. The term reflects the globalization of technology terminology, where English terms are often adopted or directly translated in technical documentation.
Related Idioms & Phrases
to separate the wheat from the chaff (distinguishing important from unimportant features)
to break down into components (to perform feature separation)
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