Código QR (código de barras bidimensional)

Clustering based feature selection using Partitioning Around Medoids (PAM)

High-dimensional data contains a large number of features. With many features, high dimensional data requires immense computational resources, including space and time. Several studies indicate that not all features of high dimensional data are relevant to classification result. Dimensionality reduc...

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Principais autores: Dewi Pramudi Ismi, Murinto Murinto
Format: Artigo
Sprog:Inglês
Udgivet: Universitas Ahmad Dahlan 2020-05-01
Serier:Jurnal Informatika
Fag:
dimensionality reduction
feature selection
clustering
partitioning around medoids (pam)
high dimensional data
Online adgang:http://journal.uad.ac.id/index.php/JIFO/article/view/17620
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