Assessing and Quantifying Clusteredness: The OPTICS Cordillera

DOI10.1080/10618600.2017.1349664OpenAlexW2227548431WikidataQ58040153 ScholiaQ58040153MaRDI QIDQ80441

Patrick Mair, Thomas Rusch, Kurt Hornik, Patrick Mair, Thomas Rusch

Publication date: 2 January 2018

Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10618600.2017.1349664

zbMATH Keywords

indexcluster analysisdimensionality reductionperception

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (4)

Cluster Optimized Proximity Scaling ⋮ cordillera ⋮ Structure-based hyperparameter selection with Bayesian optimization in multidimensional scaling ⋮ cops

Uses Software

• R
• Silhouettes
• MASS (R)
• ggplot2
• vegan
• t-SNE

Cites Work

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• CLUES: a non-parametric clustering method based on local shrinking
• Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
• Principal component analysis.
• Statistical Analysis of Financial Data in S-Plus
• The second-order analysis of stationary point processes
• A new rank correlation coefficient with application to the consensus ranking problem

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