Mining frequent patterns with an FP-tree avoids costly candidate generation and repeatedly occurrence frequency checking against the support threshold. It therefore achieves bette...
Feature selection is an important task in effective data mining. A new challenge to feature selection is the so-called “small labeled-sample problem” in which labeled data is...
In many applications, association rules will only be interesting if they represent non-trivial correlations between all constituent items. Numerous techniques have been developed ...
The paper presents a method for pruning frequent itemsets based on background knowledge represented by a Bayesian network. The interestingness of an itemset is defined as the abso...
Class membership probability estimates are important for many applications of data mining in which classification outputs are combined with other sources of information for decisi...