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» Boosting Lazy Decision Trees
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AUSAI
2006
Springer
13 years 9 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
ICDM
2006
IEEE
169views Data Mining» more  ICDM 2006»
13 years 11 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
ICTAI
2006
IEEE
13 years 11 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
COMSIS
2006
156views more  COMSIS 2006»
13 years 5 months ago
A Comparison of the Bagging and the Boosting Methods Using the Decision Trees Classifiers
In this paper we present an improvement of the precision of classification algorithm results. Two various approaches are known: bagging and boosting. This paper describes a set of ...
Kristína Machova, Miroslav Puszta, Frantise...
GIS
2010
ACM
13 years 4 months ago
Location disambiguation in local searches using gradient boosted decision trees
Local search is a specialization of the web search that allows users to submit geographically constrained queries. However, one of the challenges for local search engines is to un...
Ritesh Agrawal, James G. Shanahan