Semi-supervised clustering methods

DOI10.1002/wics.1270zbMATH Open1545.62006MaRDI QIDQ6607905

Eric Bair

Publication date: 19 September 2024

Published in: Wiley Interdisciplinary Reviews. WIREs Computational Statistics (Search for Journal in Brave)

zbMATH Keywords

cluster analysishigh-dimensional datamachine learningsemi-supervised methods

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08)

Cites Work

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• Estimating the number of clusters in a data set via the gap statistic
• Algorithm AS 136: A K-Means Clustering Algorithm
• Learning a Mahalanobis distance metric for data clustering and classification
• Semi-supervised clustering with metric learning: an adaptive kernel method
• Semi-supervised graph clustering: a kernel approach
• Text classification from labeled and unlabeled documents using EM
• Complementary hierarchical clustering
• Finding the Number of Clusters in a Dataset
• Least squares quantization in PCM
• A Framework for Feature Selection in Clustering
• The Elements of Statistical Learning

Related Items (4)

Network-based semisupervised clustering ⋮ Stability estimation for unsupervised clustering: a review ⋮ Selection of number of clusters and warping penalty in clustering functional electrocardiogram ⋮ Semi-supervised clustering of time-dependent categorical sequences with application to discovering education-based life patterns

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