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KDD
2003
ACM
156views Data Mining» more  KDD 2003»
16 years 5 months ago
Mining distance-based outliers in near linear time with randomization and a simple pruning rule
Defining outliers by their distance to neighboring examples is a popular approach to finding unusual examples in a data set. Recently, much work has been conducted with the goal o...
Stephen D. Bay, Mark Schwabacher
KDD
2003
ACM
160views Data Mining» more  KDD 2003»
16 years 5 months ago
Playing hide-and-seek with correlations
We present a method for very high-dimensional correlation analysis. The method relies equally on rigorous search strategies and on human interaction. At each step, the method cons...
Chris Jermaine
KDD
2003
ACM
175views Data Mining» more  KDD 2003»
16 years 5 months ago
Weighted Association Rule Mining using weighted support and significance framework
We address the issues of discovering significant binary relationships in transaction datasets in a weighted setting. Traditional model of association rule mining is adapted to han...
Feng Tao, Fionn Murtagh, Mohsen Farid
KDD
2001
ACM
228views Data Mining» more  KDD 2001»
16 years 5 months ago
REVI-MINER, a KDD-environment for deviation detection and analysis of warranty and goodwill cost statements in automotive indust
REVI-MINER is a KDD-environment which supports the detection and analysis of deviations in warranty and goodwill cost statements. The system was developed within the framework of ...
Edgar Hotz, Udo Grimmer, W. Heuser, Gholamreza Nak...
KDD
2001
ACM
216views Data Mining» more  KDD 2001»
16 years 5 months ago
Real world performance of association rule algorithms
This study compares five well-known association rule algorithms using three real-world datasets and an artificial dataset. The experimental results confirm the performance improve...
Zijian Zheng, Ron Kohavi, Llew Mason
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