90 search results - page 2 / 18 » AUC: A Better Measure than Accuracy in Comparing Learning Al... |
ECML
2003
Springer
14 years 21 days ago
2003
Springer
Abstract. In this work we investigate several issues in order to improve the performance of probabilistic estimation trees (PETs). First, we derive a new probability smoothing that...
ISCI
2008
13 years 7 months ago
2008
In this paper, we introduce weights into Pawlak rough set model to balance the class distribution of a data set and develop a weighted rough set based method to deal with the clas...
IJCAI
2007
13 years 9 months ago
2007
Evaluation measures play an important role in machine learning because they are used not only to compare different learning algorithms, but also often as goals to optimize in cons...
ADMA
2005
Springer
14 years 1 months ago
2005
Springer
In real-world data mining applications, an accurate ranking is same important to a accurate classification. Naive Bayes (simply NB) has been widely used in data mining as a simple...
DASFAA
2005
IEEE
14 years 1 months ago
2005
IEEE
Naive Bayes has been widely used in data mining as a simple and effective classification algorithm. Since its conditional independence assumption is rarely true, numerous algorit...