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Data Stream Mining with Limited Validation Opportunity: Towards Instrument Failure Prediction

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Big Data Analytics and Knowledge Discovery (DaWaK 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9263))

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Abstract

A data stream mining mechanism for predicting instrument failure, founded on the concept of time series analysis, is presented. The objective is to build a model that can predict instrument failure so that some mitigation can be invoked so as to prevent the failure. The proposed mechanism therefore features the interesting characteristic that there is only a limited opportunity to validate the model. The mechanism is fully described and evaluated using single and multiple attribute scenarios.

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Notes

  1. 1.

    A LIMS is a software system designed to manage laboratory operations. LIMS are used throughout the laboratory analysis industry.

  2. 2.

    The Dendrites software is available from CSols Ltd, http://www.csols.com.

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Correspondence to Frans Coenen .

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Atkinson, K., Coenen, F., Goddard, P., Payne, T., Riley, L. (2015). Data Stream Mining with Limited Validation Opportunity: Towards Instrument Failure Prediction. In: Madria, S., Hara, T. (eds) Big Data Analytics and Knowledge Discovery. DaWaK 2015. Lecture Notes in Computer Science(), vol 9263. Springer, Cham. https://doi.org/10.1007/978-3-319-22729-0_22

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  • DOI: https://doi.org/10.1007/978-3-319-22729-0_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22728-3

  • Online ISBN: 978-3-319-22729-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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