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» Decision Trees Using the Minimum Entropy-of-Error Principle
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IJCAI
1993
13 years 8 months ago
Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning
Since most real-world applications of classification learning involve continuous-valued attributes, properly addressing the discretization process is an important problem. This pa...
Usama M. Fayyad, Keki B. Irani
SDM
2010
SIAM
192views Data Mining» more  SDM 2010»
13 years 9 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
2003
IEEE
158views Data Mining» more  ICDM 2003»
14 years 22 days ago
Identifying Markov Blankets with Decision Tree Induction
The Markov Blanket of a target variable is the minimum conditioning set of variables that makes the target independent of all other variables. Markov Blankets inform feature selec...
Lewis Frey, Douglas H. Fisher, Ioannis Tsamardinos...
ICMI
2003
Springer
138views Biometrics» more  ICMI 2003»
14 years 19 days ago
Large vocabulary sign language recognition based on hierarchical decision trees
The major difficulty for large vocabulary sign language or gesture recognition lies in the huge search space due to a variety of recognized classes. How to reduce the recognition ...
Gaolin Fang, Wen Gao, Debin Zhao
VLDB
1998
ACM
120views Database» more  VLDB 1998»
13 years 11 months ago
PUBLIC: A Decision Tree Classifier that Integrates Building and Pruning
Classification is an important problem in data mining. Given a database of records, each with a class label, a classifier generates a concise and meaningful description for each c...
Rajeev Rastogi, Kyuseok Shim