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HIS
2008
15 years 3 months ago
Evolutionary Training Set Selection to Optimize C4.5 in Imbalanced Problems
Classification in imbalanced domains is a recent challenge in machine learning. We refer to imbalanced classification when data presents many examples from one class and few from ...
Salvador García, Francisco Herrera
INFORMATICALT
2002
91views more  INFORMATICALT 2002»
15 years 1 months ago
Bayesian Heuristic Approach to Scheduling
Abstract. Real life scheduling problems are solved by heuristics with parameters defined by experts, as usual. In this paper a new approach is proposed where the parameters of vari...
Jonas Mockus
103
Voted
CP
2006
Springer
15 years 5 months ago
A Simple Distribution-Free Approach to the Max k-Armed Bandit Problem
The max k-armed bandit problem is a recently-introduced online optimization problem with practical applications to heuristic search. Given a set of k slot machines, each yielding p...
Matthew J. Streeter, Stephen F. Smith
EVOW
2006
Springer
15 years 5 months ago
Divide-and-Evolve: A New Memetic Scheme for Domain-Independent Temporal Planning
An original approach, termed Divide-and-Evolve is proposed to hybridize Evolutionary Algorithms (EAs) with Operational Research (OR) methods in the domain of Temporal Planning Prob...
Marc Schoenauer, Pierre Savéant, Vincent Vi...
127
Voted
JCO
2007
100views more  JCO 2007»
15 years 1 months ago
Semi-online scheduling with "end of sequence" information
We study a variant of classical scheduling, which is called scheduling with “end of sequence” information. It is known in advance that the last job has the longest processing ...
Leah Epstein, Deshi Ye