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AUSAI
2003
Springer
13 years 10 months ago
On Why Discretization Works for Naive-Bayes Classifiers
We investigate why discretization is effective in naive-Bayes learning. We prove a theorem that identifies particular conditions under which discretization will result in naiveBay...
Ying Yang, Geoffrey I. Webb
SODA
2008
ACM
88views Algorithms» more  SODA 2008»
13 years 7 months ago
Sampling stable marriages: why spouse-swapping won't work
We study the behavior of random walks along the edges of the stable marriage lattice for various restricted families of allowable preference sets. In the "k-attribute model,&...
Nayantara Bhatnagar, Sam Greenberg, Dana Randall
ESEC
1999
Springer
13 years 10 months ago
Yesterday, My Program Worked. Today, It Does Not. Why?
Imagine some program and a number of changes. If none of these changes is applied (“yesterday”), the program works. If all changes are applied (“today”), the program does n...
Andreas Zeller
CSCW
2010
ACM
14 years 3 months ago
Why the plan doesn't hold: a study of situated planning, articulation and coordination work in a surgical ward
Most studies of plans and situated work have applied ethnographic methods and and thus fail to provide any quantitative insight into the extent of this phenomenon. We present a st...
Jakob E. Bardram, Thomas Riisgaard Hansen
WSC
1994
13 years 7 months ago
Inside simulation software: how it works and why it matters
ABSTRACT This paper provides beginning and intermediate simulation practitioners and interested simulation consumers with a grounding in how discrete-event simulation software work...
Thomas J. Schriber, Daniel T. Brunner