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» Globally Induced Model Trees: An Evolutionary Approach
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ICML
2004
IEEE
14 years 9 months ago
Lookahead-based algorithms for anytime induction of decision trees
The majority of the existing algorithms for learning decision trees are greedy--a tree is induced top-down, making locally optimal decisions at each node. In most cases, however, ...
Saher Esmeir, Shaul Markovitch
AAAI
2006
13 years 10 months ago
When a Decision Tree Learner Has Plenty of Time
The majority of the existing algorithms for learning decision trees are greedy--a tree is induced top-down, making locally optimal decisions at each node. In most cases, however, ...
Saher Esmeir, Shaul Markovitch
EMMCVPR
2001
Springer
14 years 1 months ago
Matching Free Trees, Maximal Cliques, and Monotone Game Dynamics
—Motivated by our recent work on rooted tree matching, in this paper we provide a solution to the problem of matching two free (i.e., unrooted) trees by constructing an associati...
Marcello Pelillo
SIAMCOMP
1998
111views more  SIAMCOMP 1998»
13 years 8 months ago
Computing the Local Consensus of Trees
The inference of consensus from a set of evolutionary trees is a fundamental problem in a number of fields such as biology and historical linguistics, and many models for inferrin...
Sampath Kannan, Tandy Warnow
GECCO
2006
Springer
188views Optimization» more  GECCO 2006»
14 years 7 days ago
Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach
This work describes a forward-looking approach for the solution of dynamic (time-changing) problems using evolutionary algorithms. The main idea of the proposed method is to combi...
Iason Hatzakis, David Wallace