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» Types of Cost in Inductive Concept Learning
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KDD
1995
ACM
135views Data Mining» more  KDD 1995»
13 years 9 months ago
Rough Sets Similarity-Based Learning from Databases
Manydata mining algorithms developed recently are based on inductive learning methods. Very few are based on similarity-based learning. However, similarity-based learning accrues ...
Xiaohua Hu, Nick Cercone
AAAI
1997
13 years 7 months ago
Representing Sequences in Description Logics
This paper describes an approach for representing and manipulating sequences in description logics (DLs). The key idea is to represent sequences using sux trees, then represent t...
Haym Hirsh, Daniel Kudenko
ISCI
2008
181views more  ISCI 2008»
13 years 6 months ago
Attribute reduction in decision-theoretic rough set models
Rough set theory can be applied to rule induction. There are two different types of classification rules, positive and boundary rules, leading to different decisions and consequen...
Yiyu Yao, Yan Zhao
GECCO
2008
Springer
232views Optimization» more  GECCO 2008»
13 years 7 months ago
An efficient SVM-GA feature selection model for large healthcare databases
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
Rick Chow, Wei Zhong, Michael Blackmon, Richard St...
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