k-medoides
1. A clustering algorithm in machine learning and data mining that partitions data points into k clusters by selecting actual data points (medoids) as cluster centers, minimizing the sum of distances between points and their nearest medoid
The k-medoids algorithm is more robust to outliers than k-means because it uses actual data points as centers.
O algoritmo k-medoides é mais robusto a valores atípicos do que k-means porque usa pontos de dados reais como centros.
2. A partitioning clustering method that iteratively assigns objects to the nearest medoid and updates medoids to minimize total dissimilarity
Researchers applied k-medoids clustering to segment customer behavior patterns in the dataset.
Pesquisadores aplicaram o agrupamento k-medoides para segmentar padrões de comportamento de clientes no conjunto de dados.
K-medoids is a specialized term primarily used in technical, academic, and data science contexts in both Brazil and Portugal. It is not commonly used in everyday conversation and is specific to computer science and statistics fields. The term is typically kept in English or directly transliterated in Portuguese technical literature, though formal translations exist.
Look up more words on Fala2Me
The free English-Portuguese dictionary with real Brazilian accents, NYC slang, conjugator and more
Open Fala2Me →