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» Approximation Methods for Supervised Learning
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ECML
2003
Springer
15 years 7 months ago
Logistic Model Trees
Abstract. Tree induction methods and linear models are popular techniques for supervised learning tasks, both for the prediction of nominal classes and continuous numeric values. F...
Niels Landwehr, Mark Hall, Eibe Frank
CC
2006
Springer
124views System Software» more  CC 2006»
15 years 5 months ago
Hybrid Optimizations: Which Optimization Algorithm to Use?
We introduce a new class of compiler heuristics: hybrid optimizations. Hybrid optimizations choose dynamically at compile time which optimization algorithm to apply from a set of d...
John Cavazos, J. Eliot B. Moss, Michael F. P. O'Bo...
ICMLA
2008
15 years 3 months ago
Semi-supervised IFA with Prior Knowledge on the Mixing Process: An Application to a Railway Device Diagnosis
Independent Factor Analysis (IFA) is a well known method used to recover independent components from their linear observed mixtures without any knowledge on the mixing process. Su...
Etienne Côme, Zohra Leila Cherfi, Latifa Ouk...
NAACL
2003
15 years 3 months ago
Automatic Extraction of Semantic Networks from Text using Leximancer
Leximancer is a software system for performing conceptual analysis of text data in a largely language independent manner. The system is modelled on Content Analysis and provides u...
Andrew E. Smith
AAAI
1996
15 years 3 months ago
Building Classifiers Using Bayesian Networks
Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with strong assumptions of independence among features, called naive Bayes, is competit...
Nir Friedman, Moisés Goldszmidt