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JIS
2007
95views more  JIS 2007»
14 years 11 months ago
Combined association rules for dealing with missing values
With the rapid increase in the use of databases, the problem of missing values inevitably arises. The techniques developed to effectively recover these missing values should be hi...
Jau-Ji Shen, Chin-Chen Chang, Yu-Chiang Li
ADMA
2010
Springer
248views Data Mining» more  ADMA 2010»
14 years 9 months ago
Classification Inductive Rule Learning with Negated Features
This paper reports on an investigation to compare a number of strategies to include negated features within the process of Inductive Rule Learning (IRL). The emphasis is on generat...
Stephanie Chua, Frans Coenen, Grant Malcolm
PKDD
2004
Springer
141views Data Mining» more  PKDD 2004»
15 years 5 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
JDWM
2007
90views more  JDWM 2007»
14 years 11 months ago
Mining for Mutually Exclusive Items in Transaction Databases
Association rule mining is a popular task that involves the discovery of co-occurences of items in transaction databases. Several extensions of the traditional association rule mi...
George Tzanis, Christos Berberidis
EDBT
2000
ACM
15 years 4 months ago
Quality Assessment and Uncertainty Handling in Data Mining Process
The KDD process aims at the discovery and extraction of “useful” knowledge (such as interesting patterns, classification, rules etc) from large data repositories. A widely rec...
Maria Halkidi