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» Improving Mining Quality by Exploiting Data Dependency
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ICDM
2010
IEEE
213views Data Mining» more  ICDM 2010»
14 years 9 months ago
Modeling Experts and Novices in Citizen Science Data for Species Distribution Modeling
Citizen scientists, who are volunteers from the community that participate as field assistants in scientific studies [3], enable research to be performed at much larger spatial and...
Jun Yu, Weng-Keen Wong, Rebecca A. Hutchinson
CEC
2008
IEEE
15 years 6 months ago
A Quantum-inspired Genetic Algorithm for data clustering
—The conventional K-Means clustering algorithm must know the number of clusters in advance and the clustering result is sensitive to the selection of the initial cluster centroid...
Jing Xiao, YuPing Yan, Ying Lin, Ling Yuan, Jun Zh...
106
Voted
SADM
2010
141views more  SADM 2010»
14 years 6 months ago
A parametric mixture model for clustering multivariate binary data
: The traditional latent class analysis (LCA) uses a mixture model with binary responses on each subject that are independent conditional on cluster membership. However, in many pr...
Ajit C. Tamhane, Dingxi Qiu, Bruce E. Ankenman
ICML
2010
IEEE
15 years 28 days ago
Active Learning for Networked Data
We introduce a novel active learning algorithm for classification of network data. In this setting, training instances are connected by a set of links to form a network, the label...
Mustafa Bilgic, Lilyana Mihalkova, Lise Getoor
DATAMINE
2010
133views more  DATAMINE 2010»
14 years 12 months ago
Using background knowledge to rank itemsets
Assessing the quality of discovered results is an important open problem in data mining. Such assessment is particularly vital when mining itemsets, since commonly many of the disc...
Nikolaj Tatti, Michael Mampaey