12 search results - page 2 / 3 » Partitioning Nominal Attributes in Decision Trees |
ML
2000
ACM
13 years 4 months ago
2000
ACM
The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. A numb...
PAKDD
2007
ACM
13 years 11 months ago
2007
ACM
In this paper, we study the privacy-preserving decision tree building problem on vertically partitioned data. We made two contributions. First, we propose a novel hybrid approach, ...
IJCAI
1993
13 years 6 months ago
1993
Since most real-world applications of classification learning involve continuous-valued attributes, properly addressing the discretization process is an important problem. This pa...
ECML
2003
Springer
13 years 10 months ago
2003
Springer
Abstract. Tree induction methods and linear models are popular techniques for supervised learning tasks, both for the prediction of nominal classes and continuous numeric values. F...
ICDM
2009
IEEE
13 years 11 months ago
2009
IEEE
—Methods for learning decision rules are being successfully applied to many problem domains, especially where understanding and interpretation of the learned model is necessary. ...