Evaluation methods and decision theory for classification of streaming data with temporal dependence

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Title

Evaluation methods and decision theory for classification of streaming data with temporal dependence

Content partner

University of Waikato

Collection

ResearchCommons@Waikato

Description

Predictive modeling on data streams plays an important role in modern data analysis, where data arrives continuously and needs to be mined in real time. In the stream setting the data distribution is often evolving over time, and models that update themselves during operation are becoming the state-of-the-art. This paper formalizes a learning and evaluation scheme of such predictive models. We theoretically analyze evaluation of classifiers on streaming data with temporal dependence. Our find...

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Format

Research paper

Research format

Journal article

Date created

2015

Creator

Žliobaitė, Indrė / Bifet, Albert / Read, Jesse / Pfahringer, Bernhard / Holmes, Geoffrey

URL

https://hdl.handle.net/10289/8954

Related subjects

Classification / Data streams / Evaluation / Temporal dependence / Machine learning

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This article is published in the online journal: Machine Learning. © The Authors 2014.

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