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KDD
1997
ACM
135views Data Mining» more  KDD 1997»
13 years 9 months ago
Brute-Force Mining of High-Confidence Classification Rules
This paper investigates a brute-force technique for mining classification rules from large data sets. We employ an association rule miner enhanced with new pruning strategies to c...
Roberto J. Bayardo Jr.
JIIS
2006
100views more  JIIS 2006»
13 years 5 months ago
Spatial associative classification: propositional vs structural approach
Spatial associative classification takes advantage of employing association rules for spatial classification purposes. In this work, we investigate spatial associative classificati...
Michelangelo Ceci, Annalisa Appice
DEXA
2004
Springer
153views Database» more  DEXA 2004»
13 years 10 months ago
A New Approach of Eliminating Redundant Association Rules
Two important constraints of association rule mining algorithm are support and confidence. However, such constraints-based algorithms generally produce a large number of redundant ...
Mafruz Zaman Ashrafi, David Taniar, Kate A. Smith
AMC
2008
87views more  AMC 2008»
13 years 5 months ago
Mining classification rules with Reduced MEPAR-miner Algorithm
In this study, a new classification technique based on rough set theory and MEPAR-miner algorithm for association rule mining is introduced. Proposed method is called as `Reduced ...
Emel Kizilkaya Aydogan, Cevriye Gencer
PKDD
2004
Springer
141views Data Mining» more  PKDD 2004»
13 years 10 months ago
Spatial Associative Classification at Different Levels of Granularity: A Probabilistic Approach
In this paper we propose a novel spatial associative classifier method based on a multi-relational approach that takes spatial relations into account. Classification is driven by s...
Michelangelo Ceci, Annalisa Appice, Donato Malerba