linear separatability
[/ˈlɪnɪər ˌsɛpərəˈbɪləti/]
noun
separabilidade linear
1. In machine learning and mathematics, the property of a dataset where two classes can be completely separated by a single hyperplane or linear decision boundary in a given feature space
The dataset exhibits linear separatability, allowing the support vector machine to find a perfect classification boundary.
O conjunto de dados apresenta separabilidade linear, permitindo que a máquina de vetores de suporte encontre um limite de classificação perfeito.
2. The condition in which a set of points belonging to different classes can be divided into distinct regions using only linear functions
We verified the linear separatability of our training data before applying the logistic regression model.
Verificamos a separabilidade linear dos nossos dados de treinamento antes de aplicar o modelo de regressão logística.
This is a technical term primarily used in computer science, machine learning, and mathematics education. It is standardized across both Brazilian and European Portuguese academic communities. The term gained prominence with the rise of machine learning applications and is commonly encountered in university courses on artificial intelligence and data science.
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