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AUSAI
2006
Springer
15 years 3 months ago
Lazy Learning for Improving Ranking of Decision Trees
Decision tree-based probability estimation has received great attention because accurate probability estimation can possibly improve classification accuracy and probability-based r...
Han Liang, Yuhong Yan
SDM
2010
SIAM
192views Data Mining» more  SDM 2010»
15 years 1 months ago
Fast and Accurate Gene Prediction by Decision Tree Classification
Gene prediction is one of the most challenging tasks in genome analysis, for which many tools have been developed and are still evolving. In this paper, we present a novel gene pr...
Rong She, Jeffrey Shih-Chieh Chu, Ke Wang, Nanshen...
ICDM
2010
IEEE
127views Data Mining» more  ICDM 2010»
14 years 9 months ago
Learning Markov Network Structure with Decision Trees
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Daniel Lowd, Jesse Davis
KDD
1995
ACM
176views Data Mining» more  KDD 1995»
15 years 3 months ago
MDL-Based Decision Tree Pruning
This paper explores the application of the Minimum Description Length principle for pruning decision trees. We present a new algorithm that intuitively captures the primary goal o...
Manish Mehta 0002, Jorma Rissanen, Rakesh Agrawal
MSR
2006
ACM
15 years 5 months ago
Predicting defect densities in source code files with decision tree learners
With the advent of open source software repositories the data available for defect prediction in source files increased tremendously. Although traditional statistics turned out t...
Patrick Knab, Martin Pinzger, Abraham Bernstein