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JMS
2010
65views more  JMS 2010»
15 years 4 months ago
A Tree-Based Decision Model to Support Prediction of the Severity of Asthma Exacerbations in Children
This paper describes the development of a tree-based decision model to predict the severity of pediatric asthma exacerbations in the emergency department (ED) at two hours followi...
Ken Farion, Wojtek Michalowski, Szymon Wilk, Dympn...
ICML
1999
IEEE
16 years 7 months ago
Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees
Lbr is a lazy semi-naive Bayesian classi er learning technique, designed to alleviate the attribute interdependence problem of naive Bayesian classi cation. To classify a test exa...
Zijian Zheng, Geoffrey I. Webb, Kai Ming Ting
SIGIR
2005
ACM
15 years 11 months ago
Boosted decision trees for word recognition in handwritten document retrieval
Recognition and retrieval of historical handwritten material is an unsolved problem. We propose a novel approach to recognizing and retrieving handwritten manuscripts, based upon ...
Nicholas R. Howe, Toni M. Rath, R. Manmatha
CSDA
2006
91views more  CSDA 2006»
15 years 6 months ago
Maximum a posteriori pruning on decision trees and its application to bootstrap BUMPing
The cost-complexity pruning generates nested subtrees and selects the best one. However, its computational cost is large since it uses holdout sample or cross-validation. On the o...
Jinseog Kim, Yongdai Kim
GECCO
2004
Springer
152views Optimization» more  GECCO 2004»
15 years 11 months ago
Ant System for the k-Cardinality Tree Problem
This paper gives an algorithm for finding the minimum weight tree having k edges in an edge weighted graph. The algorithm combines a search and optimization technique based on phe...
Thang Nguyen Bui, Gnanasekaran Sundarraj