Recovery Levels of Clustering Algorithms Using Different Similarity Measures for Functional Data |
Chae, Seong San
(Department of Information and Statistics, Daejeon University)
Kim, Chansoo (Department of Statistics, Oklahoma State University) Warde, William D. (Department of Statistics, Oklahoma State university) |
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Robust cluster analysis of microarray gene expression data with the number of clusters determined biologically
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A method to predict the number of clusters
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Shrinkage-based smilarity metric for cluster analysis of microarray data
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DOI ScienceOn |
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Cluster analysis and display of genome-wide expression patterns
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A method for comparing two hierarchical clusterings
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DOI ScienceOn |
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Some distance properties of latent root and vector mehtods used in multivariate analysis
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DOI |
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A mathematical comparison of the members of an infinite family of agglomerative clustering algorithms
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DOI |
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Distinctive gene expression patterns in human mammary epithelial cells and breast cancers
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DOI ScienceOn |
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Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization
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DOI |
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Analysing gene expression data from DNA microarrays to identify candidate genes
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DOI ScienceOn |
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Some distributional results concerning a comparative statistic used in cluster analysis
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A comparison of agglomerative clustering method with respect to noise
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DOI ScienceOn |
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Moments of Rand's C Statistic in cluster analysis
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Agglomerative hierarchical clustering of continuous variables based on mutual information
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DOI ScienceOn |
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Transcriptional profiling of bone regeneration; insight into the molecular complexity of wound repair
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DOI ScienceOn |
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Statistical methods for gene expression data
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Objective criteria for the evaluation of clustering methods
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DOI ScienceOn |
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