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IFIP12
2008
14 years 11 months ago
P-Prism: A Computationally Efficient Approach to Scaling up Classification Rule Induction
Top Down Induction of Decision Trees (TDIDT) is the most commonly used method of constructing a model from a dataset in the form of classification rules to classify previously unse...
Frederic T. Stahl, Max A. Bramer, Mo Adda
72
Voted
ISMB
1993
14 years 11 months ago
The Induction of Rules for Predicting Chemical Carcinogenesis in Rodents
This paper presents results from an ongoing effort in applying a variety of induction-based methods to the problem of predicting the biological activity of noncongeneric (structu...
Dennis Bahler, Douglas W. Bristol
SDM
2009
SIAM
112views Data Mining» more  SDM 2009»
15 years 7 months ago
A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning.
Most commonly used inductive rule learning algorithms employ a hill-climbing search, whereas local pattern discovery algorithms employ exhaustive search. In this paper, we evaluat...
Frederik Janssen, Johannes Fürnkranz
ENGL
2007
71views more  ENGL 2007»
14 years 9 months ago
Inductive Classifying Artificial Network for Fly Ash Type Categorization
Nowadays, fly ash is a common ingredient of concrete and may constitute up to 50% by weight of the total binder material. Incorporation of fly ash in Portland-cement concrete is hi...
M. C. Nataraja, M. A. Jayaram, C. N. Ravikumar
ICDE
2005
IEEE
113views Database» more  ICDE 2005»
15 years 11 months ago
On the Optimal Ordering of Maps and Selections under Factorization
The query optimizer of a database system is confronted with two aspects when handling user-defined functions (UDFs) in query predicates: the vast differences in evaluation costs b...
Thomas Neumann, Sven Helmer, Guido Moerkotte