Detecting outliers in a large set of data objects is a major data mining task aiming at finding different mechanisms responsible for different groups of objects in a data set. All...
Hans-Peter Kriegel, Matthias Schubert, Arthur Zime...
We introduce a new approach to analyzing click logs by examining both the documents that are clicked and those that are bypassed--documents returned higher in the ordering of the ...
Atish Das Sarma, Sreenivas Gollapudi, Samuel Ieong
We propose a family of novel cost-sensitive boosting methods for multi-class classification by applying the theory of gradient boosting to p-norm based cost functionals. We establ...
Knowledge Discovery in time series usually requires symbolic time series. Many discretization methods that convert numeric time series to symbolic time series ignore the temporal ...
In this paper we study the problem of constructing accurate decision tree models from data streams. Data streams are incremental tasks that require incremental, online, and any-ti...