Titlebook: Stream Data Mining: Algorithms and Their Probabilistic Properties; Leszek Rutkowski,Maciej Jaworski,Piotr Duda Book 2020 Springer Nature S

旁觀者

DEFER

inspiration

select, implement, and analyze a group sequential stopping rule. Throughout, we illustrate trial design and monitoring in the context of a group sequential survival trial of an experimental monoclonal antibody in patients with relapsed chronic lymphocytic leukemia (CLL).

irreparable

Vsd168

Book 2020y, an extremely challenging problem that involves designing ensembles and automatically choosing their sizes is described and solved. Given its scope, the book is intended for a professional audience of researchers and practitioners who dealwith stream data, e.g. in telecommunication, banking, and sensor networks..

在駕駛

Hybrid Splitting Criteria a new kind of splitting criteria can be proposed, which combine together two different single criteria in a heuristic manner. We refer to them as hybrid splitting criteria. In this chapter, we discuss premises which demonstrate that such an approach may lead to satisfactory results.

ABIDE

Classificationoduced modification allows increasing the diversity of the ensemble components. The problem of selection component is an essential issue for every ensemble algorithm [.,.,.,.,.,.,.,.], however, only few of them are not heuristic procedures [., .].

HALO

Gingivitis

multiply

Misclassification Error Impurity Measureum of random variables. In this chapter, a split measure based on the misclassification error impurity measure is proposed [., .], which has the mentioned above property. In the case of misclassification error, the bounds obtained using the Hoeffding’s inequality and the McDiarmid’s inequality are equivalent.