Scale-invariant clustering with minimum volume ellipsoids

DOI10.1016/j.cor.2006.07.001zbMath1142.62042OpenAlexW2072719263WikidataQ59592382 ScholiaQ59592382MaRDI QIDQ941528

Mahesh Kumar, James B. Orlin

Publication date: 1 September 2008

Published in: Computers \& Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cor.2006.07.001

zbMATH Keywords

outliersrobust clusteringminimum volume ellipsoidscale-invariant clustering

Mathematics Subject Classification ID

Related Items (4)

Clustering via minimum volume ellipsoids ⋮ A review of robust clustering methods ⋮ A novel scale-invariant, dynamic method for hierarchical clustering of data affected by measurement uncertainty ⋮ Affine-transformation invariant clustering models

Uses Software

• Matlab
• mclust

Cites Work

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• Outlier detection in the multiple cluster setting using the minimum covariance determinant estimator
• The multivariate normal distribution
• A comparison of SOM neural network and hierarchical clustering methods
• Pattern separation by convex programming
• Detection of Outliers in Multivariate Data: A Method Based on Clustering and Robust Estimators
• Determinant Maximization with Linear Matrix Inequality Constraints
• Model-Based Clustering, Discriminant Analysis, and Density Estimation
• An Algorithm for Separating Patterns by Ellipsoids
• Computation of Minimum-Volume Covering Ellipsoids

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