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» Discovering associations with numeric variables
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ML
2008
ACM
13 years 5 months ago
Layered critical values: a powerful direct-adjustment approach to discovering significant patterns
Standard pattern discovery techniques, such as association rules, suffer an extreme risk of finding very large numbers of spurious patterns for many knowledge discovery tasks. The...
Geoffrey I. Webb
ML
2008
ACM
13 years 5 months ago
Discovering significant patterns
Pattern discovery techniques, such as association rule discovery, explore large search spaces of potential patterns to find those that satisfy some user-specified constraints. Due...
Geoffrey I. Webb
UAI
2008
13 years 6 months ago
Discovering Cyclic Causal Models by Independent Components Analysis
We generalize Shimizu et al's (2006) ICA-based approach for discovering linear non-Gaussian acyclic (LiNGAM) Structural Equation Models (SEMs) from causally sufficient, conti...
Gustavo Lacerda, Peter Spirtes, Joseph Ramsey, Pat...
ICMCS
2009
IEEE
199views Multimedia» more  ICMCS 2009»
13 years 3 months ago
Association rule mining in multiple, multidimensional time series medical data
Time series pattern mining (TSPM) finds correlations or dependencies in same series or in multiple time series. When the numerous instances of multiple time series data are associ...
Gaurav N. Pradhan, B. Prabhakaran
DMIN
2006
144views Data Mining» more  DMIN 2006»
13 years 6 months ago
Discovering Assignment Rules in Workforce Schedules Using Data Mining
Discovering hidden patterns in large sets of workforce schedules to gain insight into the potential knowledge in workforce schedules are crucial to better understanding the workfor...
Jihong Yan