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IADIS
2008
15 years 5 months ago
Fuzzy Association Rule Reduction Using Clustering In Som Neural Network
The major drawback of fuzzy data mining is that after applying fuzzy data mining on the quantitative data, the number of extracted fuzzy association rules is very huge. When many ...
Marjan Kaedi, Mohammad Ali Nematbakhsh, Nasser Gha...
BMCBI
2008
115views more  BMCBI 2008»
15 years 4 months ago
Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient
Background: Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson corre...
Jianchao Yao, Chunqi Chang, Mari L. Salmi, Yeung S...
BMCBI
2006
119views more  BMCBI 2006»
15 years 4 months ago
LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates
Background: Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to iden...
Guoli Wang, Andrew V. Kossenkov, Michael F. Ochs
CCGRID
2008
IEEE
15 years 11 months ago
Data Consolidation: A Task Scheduling and Data Migration Technique for Grid Networks
In this work we examine a task scheduling and data migration problem for Grid Networks, which we refer to as the Data Consolidation (DC) problem. DC arises when a task needs for i...
Panagiotis C. Kokkinos, Kostas Christodoulopoulos,...
KDD
2009
ACM
239views Data Mining» more  KDD 2009»
16 years 5 months ago
Tell me something I don't know: randomization strategies for iterative data mining
There is a wide variety of data mining methods available, and it is generally useful in exploratory data analysis to use many different methods for the same dataset. This, however...
Heikki Mannila, Kai Puolamäki, Markus Ojala, ...