Most decision tree algorithms base their splitting decisions on a piecewise constant model. Often these splitting algorithms are extrapolated to trees with non-constant models at ...
David S. Vogel, Ognian Asparouhov, Tobias Scheffer
In this paper we discuss a data mining framework for constructing intrusion detection models. The key ideas are to mine system audit data for consistent and useful patterns of pro...
This paper presents a new prediction model for predicting when an online customer leaves a current page and which next Web page the customer will visit. The model can forecast the ...
The problem of missing data is ubiquitous in domains such as biomedical signal processing, network traffic analysis, bibliometrics, social network analysis, chemometrics, computer...
Evrim Acar, Daniel M. Dunlavy, Tamara G. Kolda, Mo...
We present an approach for learning models that obtain accurate classification of large scale data objects, collected in spatiotemporal domains. The model generation is structured ...
Igor Vainer, Sarit Kraus, Gal A. Kaminka, Hamutal ...