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IFIP12
2008
15 years 4 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
ISMB
1993
15 years 4 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»
16 years 8 days 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»
15 years 3 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»
16 years 4 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