- This paper demonstrates how methods borrowed from information fusion can improve the performance of a classifier by constructing (i.e., fusing) new features that are combinations...
Abstract - Data mining is used regularly in a variety of industries and is continuing to gain in both popularity and acceptance. However, applying data mining methods to complex re...
Support vector machines are a valuable tool for making classifications, but their black-box nature means that they lack the natural explanatory value that many other classifiers po...
David Barbella, Sami Benzaid, Janara M. Christense...
-- The proliferation of social networks, where individuals share private information, has caused, in the last few years, a growth in the volume of sensitive data being stored in th...
Record linkage is the problem of identifying similar records across different data sources. The similarity between two records is defined based on domain-specific similarity functi...
While the emerging field of privacy preserving data mining (PPDM) will enable many new data mining applications, it suffers from several practical difficulties. PPDM algorithms are...
Jimmy Secretan, Anna Koufakou, Michael Georgiopoul...
Typical methods in CRM marketing include action selection on the basis of Markov Decision Processes with fixed transition probabilities on the one hand, and scoring customers separ...
This paper proposes a new method to detect abnormal process state. The method is based on cluster center point monitoring in time and is demonstrated in its application to data fro...
- This short paper compares the performance of three popular decision tree algorithms: C4.5, C5.0, and WEKA's J48. These decision tree algorithms are all related in that C5.0 ...
Samuel Moore, Daniel D'Addario, James Kurinskas, G...
In high dimensional data sets not all dimensions contain an equal amount of information and most of the time global features are more important than local differences. This makes ...