GAP: a graphical environment for matrix visualization and cluster analysis

DOI10.1016/j.csda.2008.09.029zbMath1464.62013OpenAlexW2160854065MaRDI QIDQ962314

Chun-Houh Chen, Han-Ming Wu, Yin-Jing Tien

Publication date: 6 April 2010

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2008.09.029

Mathematics Subject Classification ID

Software, source code, etc. for problems pertaining to statistics (62-04) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Graphical methods in statistics (62A09)

Related Items (7)

Exploratory data analysis of interval-valued symbolic data with matrix visualization ⋮ Explaining mixture models through semantic pattern mining and banded matrix visualization ⋮ On the strengths of the self-updating process clustering algorithm ⋮ Editorial: Second special issue on statistical algorithms and software ⋮ Two-way incremental seriation in the temporal domain with three-dimensional visualization: making sense of evolving high-dimensional datasets ⋮ Isometric sliced inverse regression for nonlinear manifold learning ⋮ GAP

Uses Software

• R
• DIVCLUS-T
• Silhouettes
• seriation
• AS 136
• impute

Cites Work

• Algorithm AS 136: A K-Means Clustering Algorithm
• DIVCLUS-T: a monothetic divisive hierarchical clustering method
• Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
• The plane with parallel coordinates
• Well-Separated Clusters and Optimal Fuzzy Partitions
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