Transcript Complex methods in clustering and classification

Complex methods in clustering
and classification
• Techniques for the future
• Worth “keep-trying”; But
• No convincing evidence of dominant
performance, globally or locally
• Simplicity/complexity is crucial
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Review
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Linkage : Eisen et al ,
Alon et al
K-mean : Tavazoein et al
Self-organizing map : Tamayo et al
SVD : Holter et al; Alter, Brown, Botstein
Support vector machine (classification)
Finding Gene clusters
• K-mean versus self-organization map
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how to fine-tune user-specified parameters-need some
theoretical guidance
What is a cluster ? Criteria needed
normal mixture, (hidden) indicator
PLAID model ( Statistica Sinica 2002, Lazzeroni, Owen)
Gene shaving (Hastie, Tibshirani, et. al)
PCA plot, projection pursuit, grand tour
Y-guided clustering (SIR/PHD, under investigation)
MDS( bi-plot forcategorical responses, showing both
cases (genes) and variables(different clustering methods),
displaying results from many different clustering
procedures)
Seriation and row-column sorting
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Hierarchical clustering
Others
Generalized association plot (Chen 2001)
Sharp boundaries may be artifacts due to
“clever” permutation