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SODA
2010
ACM
189views Algorithms» more  SODA 2010»
16 years 2 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»
15 years 5 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»
16 years 6 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
15 years 7 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
16 years 3 days 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