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Algoritma Clustering Unsupervised Machine Learning: cara kerja dan contoh kode implementasi

Saludin Muis - Personal Name;

"Buku ini membahas konsep clustering dalam unsupervised learning sebagai metode pengelompokan data tanpa label. Tujuannya adalah menemukan pola dan struktur

alami dalam dataset dengan mengelompokkan data berdasarkan kesamaan

karakteristik. Berbagai algoritma populer dijelaskan, seperti K-Means,

Hierarchical Clustering, DBSCAN, Mean Shift, Gaussian Mixture Model (GMM),

Spectral Clustering, dan Agglomerative Clustering. Setiap metode memiliki

pendekatan unik dalam membentuk cluster, baik berbasis jarak, kepadatan,

maupun probabilitas. Melalui clustering, data kompleks dapat diorganisasi

menjadi kelompok bermakna yang bermanfaat untuk analisis, segmentasi, dan

pengambilan keputusan dalam berbagai bidang aplikasi machine learning."


Availability
#
Library PEI 006.3 SAL a
202610019
Available
Detail Information
Series Title
-
Call Number
006.3 SAL a
Publisher
Yogyakarta : Teknosain., 2026
Collation
xii, 152 hlm. ; 24 cm
Language
Indonesia
ISBN/ISSN
9786347198921
Classification
006
Content Type
-
Media Type
-
Carrier Type
-
Edition
Ed. 1, Cet. 1
Subject(s)
Machine Learning
Specific Detail Info
-
Statement of Responsibility
-
Other version/related

No other version available

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