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SODA
2010
ACM
189views Algorithms» more  SODA 2010»
14 years 7 months ago
Correlation Clustering with Noisy Input
Correlation clustering is a type of clustering that uses a basic form of input data: For every pair of data items, the input specifies whether they are similar (belonging to the s...
Claire Mathieu, Warren Schudy
BIOINFORMATICS
2007
190views more  BIOINFORMATICS 2007»
13 years 10 months ago
Towards clustering of incomplete microarray data without the use of imputation
Motivation: Clustering technique is used to find groups of genes that show similar expression patterns under multiple experimental conditions. Nonetheless, the results obtained by...
Dae-Won Kim, Ki Young Lee, Kwang H. Lee, Doheon Le...
KDD
2004
ACM
103views Data Mining» more  KDD 2004»
14 years 10 months ago
An objective evaluation criterion for clustering
We propose and test an objective criterion for evaluation of clustering performance: How well does a clustering algorithm run on unlabeled data aid a classification algorithm? The...
Arindam Banerjee, John Langford
SEC
2007
13 years 11 months ago
Exploratory survey on an Evaluation Model for a Sense of Security
Research in information security is no longer limited to technical issues: human-related issues such as trust and the sense of security are also required by the user. In this paper...
Natsuko Hikage, Yuko Murayama, Carl Hauser
ICTIR
2009
Springer
14 years 4 months ago
A New Measure of the Cluster Hypothesis
Abstract. We have found that the nearest neighbor (NN) test is an insufficient measure of the cluster hypothesis. The NN test is a local measure of the cluster hypothesis. Designer...
Mark D. Smucker, James Allan