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ICDM
2010
IEEE
127views Data Mining» more  ICDM 2010»
13 years 6 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
METMBS
2004
151views Mathematics» more  METMBS 2004»
13 years 10 months ago
Machine Learning Techniques for the Evaluation of External Skeletal Fixation Structures
In this thesis we compare several machine learning techniques for evaluating external skeletal fixation proposals. We experimented in the context of dog bone fractures but the pot...
Ning Suo, Khaled Rasheed, Walter D. Potter, Dennis...
SDM
2008
SIAM
157views Data Mining» more  SDM 2008»
13 years 10 months ago
ROC-tree: A Novel Decision Tree Induction Algorithm Based on Receiver Operating Characteristics to Classify Gene Expression Data
Gene expression information from microarray experiments is a primary form of data for biological analysis and can offer insights into disease processes and cellular behaviour. Suc...
M. Maruf Hossain, Md. Rafiul Hassan, James Bailey
EMNLP
2004
13 years 10 months ago
A Boosting Algorithm for Classification of Semi-Structured Text
The focus of research in text classification has expanded from simple topic identification to more challenging tasks such as opinion/modality identification. Unfortunately, the la...
Taku Kudo, Yuji Matsumoto
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