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ESWA
2006
122views more  ESWA 2006»
13 years 8 months ago
Transmembrane segments prediction and understanding using support vector machine and decision tree
In recent years, there have been many studies focusing on improving the accuracy of prediction of transmembrane segments, and many significant results have been achieved. In spite...
Jieyue He, Hae-Jin Hu, Robert W. Harrison, Phang C...
VLDB
1998
ACM
95views Database» more  VLDB 1998»
14 years 28 days ago
RainForest - A Framework for Fast Decision Tree Construction of Large Datasets
Classification of large datasets is an important data mining problem. Many classification algorithms have been proposed in the literature, but studies have shown that so far no al...
Johannes Gehrke, Raghu Ramakrishnan, Venkatesh Gan...
COCO
1991
Springer
112views Algorithms» more  COCO 1991»
14 years 7 days ago
Randomized vs.Deterministic Decision Tree Complexity for Read-Once Boolean Functions
We consider the deterministic and the randomized decision tree complexities for Boolean functions, denoted DC(f) and RC(f), respectively. A major open problem is how small RC(f) ca...
Rafi Heiman, Avi Wigderson
PAMI
2007
166views more  PAMI 2007»
13 years 8 months ago
A Comparison of Decision Tree Ensemble Creation Techniques
Abstract—We experimentally evaluate bagging and seven other randomizationbased approaches to creating an ensemble of decision tree classifiers. Statistical tests were performed o...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...
ICTAI
2006
IEEE
14 years 2 months ago
Improve Decision Trees for Probability-Based Ranking by Lazy Learners
Existing work shows that classic decision trees have inherent deficiencies in obtaining a good probability-based ranking (e.g. AUC). This paper aims to improve the ranking perfor...
Han Liang, Yuhong Yan