sparse solution
[/spɑːrs səˈluːʃən/]
nounpl: sparse solutions
solução esparsa
1. A mathematical or computational solution where most variables or components are zero, with only a few non-zero elements
The optimization algorithm found a sparse solution with only 5 non-zero coefficients out of 1000 variables.
O algoritmo de otimização encontrou uma solução esparsa com apenas 5 coeficientes não-nulos de 1000 variáveis.
2. In machine learning and statistics, a model or result that achieves good performance with minimal features or parameters
Sparse solutions are preferred in feature selection because they are more interpretable and computationally efficient.
Soluções esparsas são preferidas na seleção de características porque são mais interpretáveis e computacionalmente eficientes.
3. A result of regularization techniques such as L1 (Lasso) that penalizes non-zero coefficients to reduce model complexity
The Lasso regression produces a sparse solution by shrinking some coefficients exactly to zero.
A regressão Lasso produz uma solução esparsa reduzindo alguns coeficientes exatamente a zero.
This is primarily technical terminology used in academic and professional contexts in both Brazil and the USA. It is especially prevalent in machine learning, optimization theory, and signal processing fields. The term reflects the growing importance of efficient computational methods and interpretable models in data science.
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