143 search results - page 1 / 29 » Lazy Learning for Improving Ranking of Decision Trees |
AUSAI
2006
Springer
13 years 8 months ago
2006
Springer
Decision tree-based probability estimation has received great attention because accurate probability estimation can possibly improve classification accuracy and probability-based r...
ICML
2003
IEEE
14 years 5 months ago
2003
IEEE
This paper explores the problem of how to construct lazy decision tree ensembles. We present and empirically evaluate a relevancebased boosting-style algorithm that builds a lazy ...
ICTAI
2006
IEEE
13 years 11 months ago
2006
IEEE
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...
ICML
1999
IEEE
14 years 5 months ago
1999
IEEE
Lbr is a lazy semi-naive Bayesian classi er learning technique, designed to alleviate the attribute interdependence problem of naive Bayesian classi cation. To classify a test exa...
ICML
2009
IEEE
13 years 11 months ago
2009
IEEE
The label ranking problem consists of learning a model that maps instances to total orders over a finite set of predefined labels. This paper introduces new methods for label ra...