LAUSR

Continually trained life-long classification

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1 Published in 2022 at "Neural Computing and Applications"

DOI: 10.1007/s00521-021-06154-9

Abstract: Two challenges can be found in a life-long classifier that learns continually: the concept drift, when the probability distribution of data is changing in time, and catastrophic forgetting when the earlier learned knowledge is lost.… read more here.

Keywords: life; concept drift; catastrophic forgetting; long classification ... See more keywords

Efficient quantile tracking using an oracle

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3 Published in 2022 at "Applied Intelligence"

DOI: 10.1007/s10489-022-03489-1

Abstract: Concept drift is a well-known issue that arises when working with data streams. In this paper, we present a procedure that allows a quantile tracking procedure to cope with concept drift. We suggest using expected… read more here.

Keywords: tracking using; concept drift; efficient quantile; quantile tracking ... See more keywords

Concept drift over geological times: predictive modeling baselines for analyzing the mammalian fossil record

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0 Published in 2018 at "Data Mining and Knowledge Discovery"

DOI: 10.1007/s10618-018-0606-6

Abstract: Fossils are the remains organisms from earlier geological periods preserved in sedimentary rock. The global fossil record documents and characterizes the evidence about organisms that existed at different times and places during the Earth’s history.… read more here.

Keywords: concept drift; fossil record; fossil; geological times ... See more keywords

Analyzing and repairing concept drift adaptation in data stream classification

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0 Published in 2021 at "Machine Learning"

DOI: 10.1007/s10994-021-05993-w

Abstract: Data collected over time often exhibit changes in distribution, or concept drift, caused by changes in factors relevant to the classification task, e.g. weather conditions. Incorporating all relevant factors into the model may be able… read more here.

Keywords: drift adaptation; data stream; concept drift; drift ... See more keywords

Unsupervised concept drift detection based on multi-scale slide windows

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1 Published in 2021 at "Ad Hoc Networks"

DOI: 10.1016/j.adhoc.2020.102325

Abstract: Abstract In the past few decades, research related to concept drift learning has been increasing, and many concept drift learning algorithms have also been developed and applied to actual data stream processing. In general, concept… read more here.

Keywords: concept drift; drift; drift detection; multi scale ... See more keywords

A taxonomic look at instance-based stream classifiers

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0 Published in 2018 at "Neurocomputing"

DOI: 10.1016/j.neucom.2018.01.062

Abstract: Abstract Large numbers of data streams are today generated in many fields. A key challenge when learning from such streams is the problem of concept drift. Many methods, including many prototype methods, have been proposed… read more here.

Keywords: concept drift; taxonomic look; based stream; instance based ... See more keywords

Learning in the presence of class imbalance and concept drift

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1 Published in 2019 at "Neurocomputing"

DOI: 10.1016/j.neucom.2019.01.080

Abstract: Accepted papers will be published in our Workshop proceeding. The authors will be invited to submit an extended version to the special issue published in Neurocomputing or Connection Science (confirmed). With the wide application of… read more here.

Keywords: concept drift; imbalance concept; class imbalance;

Adaptive learning on mobile network traffic data

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1 Published in 2019 at "Connection Science"

DOI: 10.1080/09540091.2018.1512557

Abstract: ABSTRACT Machine learning based mobile traffic classification has become a popular topic in recent years. As mobile traffic data is dynamic in nature, the static model has become ineffective for the task of classifying future… read more here.

Keywords: concept drift; traffic; classification; model ... See more keywords

Learning from data streams and class imbalance

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1 Published in 2019 at "Connection Science"

DOI: 10.1080/09540091.2019.1572975

Abstract: With the wide application of machine learning algorithms to the real world, class imbalanceandconceptdrift havebecomecrucial learning issues. Applications in variousdomains such as riskmanagement, anomaly detection, fraud detection, software engineering, social media mining, and recommender systems… read more here.

Keywords: concept drift; data streams; class; class imbalance ... See more keywords

Evolutionary approaches to the concept of drift in policy studies

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1 Published in 2019 at "Critical Policy Studies"

DOI: 10.1080/19460171.2017.1414618

Abstract: ABSTRACT This article is a contribution to the emerging line of scholarly inquiry into the concept of drift in the study of public policy. It investigates a persistent problem in the literature on policy drift:… read more here.

Keywords: concept drift; drift; policy; policy studies ... See more keywords

Concept drift detection in toxicology datasets using discriminative subgraph-based drift detector

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1 Published in 2022 at "Briefings in bioinformatics"

DOI: 10.1093/bib/bbac506

Abstract: Due to the increasing importance of graphs and graph streams in data representation in today's era, concept drift detection in graph streaming scenarios is more important than ever. Contributions to concept drift detection in graph… read more here.

Keywords: toxicology; drift detection; graph; concept drift ... See more keywords