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TKDE
2008
112views more  TKDE 2008»
8 years 11 months ago
IDD: A Supervised Interval Distance-Based Method for Discretization
This paper introduces a new method for supervised discretization based on interval distances by using a novel concept of neighborhood in the target's space. The proposed metho...
Francisco J. Ruiz, Cecilio Angulo, Núria Ag...
BMCBI
2010
152views more  BMCBI 2010»
8 years 11 months ago
Comparative study of discretization methods of microarray data for inferring transcriptional regulatory networks
Background: Microarray data discretization is a basic preprocess for many algorithms of gene regulatory network inference. Some common discretization methods in informatics are us...
Yong Li, Lili Liu, Xi Bai, Hua Cai, Wei Ji, Dianji...
ICDM
2007
IEEE
136views Data Mining» more  ICDM 2007»
9 years 2 months ago
Data Discretization Unification
Data discretization is defined as a process of converting continuous data attribute values into a finite set of intervals with minimal loss of information. In this paper, we prove...
Ruoming Jin, Yuri Breitbart, Chibuike Muoh
SSPR
1998
Springer
9 years 3 months ago
Multi-interval Discretization Methods for Decision Tree Learning
Properly addressing the discretization process of continuos valued features is an important problem during decision tree learning. This paper describes four multi-interval discreti...
Petra Perner, Sascha Trautzsch
MLDM
2005
Springer
9 years 4 months ago
Multivariate Discretization by Recursive Supervised Bipartition of Graph
Abstract. In supervised learning, discretization of the continuous explanatory attributes enhances the accuracy of decision tree induction algorithms and naive Bayes classi´Čüer. M...
Sylvain Ferrandiz, Marc Boullé
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