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» The Alternating Decision Tree Learning Algorithm
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ICML
2004
IEEE
15 years 10 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
89
Voted
ICML
2003
IEEE
15 years 10 months ago
Boosting Lazy Decision Trees
This paper explores the problem of how to construct lazy decision tree ensembles. We present and empirically evaluate a relevancebased boosting-style algorithm that builds a lazy ...
Xiaoli Zhang Fern, Carla E. Brodley
69
Voted
COLT
2003
Springer
15 years 2 months ago
Learning Random Log-Depth Decision Trees under the Uniform Distribution
We consider three natural models of random logarithmic depth decision trees over Boolean variables. We give an efficient algorithm that for each of these models learns all but an ...
Jeffrey C. Jackson, Rocco A. Servedio
IEAAIE
1995
Springer
15 years 1 months ago
Polygonal Inductive Generalisation System
Classification learning has been dominated by the induction of axisorthogonal decision surfaces. While induction of alternate forms of decision surface has received some attentio...
Douglas A. Newlands, Geoffrey I. Webb
ICDM
2006
IEEE
169views Data Mining» more  ICDM 2006»
15 years 3 months ago
Privacy-Preserving Data Imputation
In this paper, we investigate privacy-preserving data imputation on distributed databases. We present a privacypreserving protocol for filling in missing values using a lazy deci...
Geetha Jagannathan, Rebecca N. Wright