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» A Hellinger-based discretization method for numeric attribut...
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KDD
2006
ACM
123views Data Mining» more  KDD 2006»
14 years 6 months ago
Mining rank-correlated sets of numerical attributes
We study the mining of interesting patterns in the presence of numerical attributes. Instead of the usual discretization methods, we propose the use of rank based measures to scor...
Toon Calders, Bart Goethals, Szymon Jaroszewicz
ICML
1999
IEEE
14 years 6 months ago
Making Better Use of Global Discretization
Before applying learning algorithms to datasets, practitioners often globally discretize any numeric attributes. If the algorithm cannot handle numeric attributes directly, prior ...
Eibe Frank, Ian H. Witten
ICML
2002
IEEE
14 years 6 months ago
Non-Disjoint Discretization for Naive-Bayes Classifiers
Previous discretization techniques have discretized numeric attributes into disjoint intervals. We argue that this is neither necessary nor appropriate for naive-Bayes classifiers...
Ying Yang, Geoffrey I. Webb
GECCO
2004
Springer
13 years 11 months ago
Experimental Evaluation of Discretization Schemes for Rule Induction
This paper proposes an experimental evaluation of various discretization schemes in three different evolutionary systems for inductive concept learning. The various discretization...
Jesús S. Aguilar-Ruiz, Jaume Bacardit, Fede...
COR
2006
97views more  COR 2006»
13 years 6 months ago
Evaluating the performance of cost-based discretization versus entropy- and error-based discretization
Discretization is defined as the process that divides continuous numeric values into intervals of discrete categorical values. In this article, the concept of cost-based discretiz...
Davy Janssens, Tom Brijs, Koen Vanhoof, Geert Wets