PROCEEDINGS IPMU '08
Lowering Uncertainty of Cancer Classification
Oleg Okun, Helen Priisalu
A new ensemble scheme is proposed
for classifying high dimensional
data, which exploits dependence
between data complexity, determining
how difficult to classify a
given dataset, and classification error.
As a classification task, gene expression
based cancer classification
is studied, with a k-nearest neighbor
as a base classifier. Experiments carried
out on five datasets show the
importance of taking into account
dataset complexity when constructing
ensembles of nearest neighbors.
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