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Multiclass Weighted Associative Classifier with Application-Based Rule Selection for Data Gathered Using Wireless Sensor Networks

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Evolutionary Computing and Mobile Sustainable Networks

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 53))

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Abstract

The twenty-first century has seen an explosion in the amount of data that is available to decision-makers. Wireless Sensor Networks are everywhere continuously collecting and feeding data to various systems. Translating these enormous amounts of data into information and making decisions quickly and effectively is a constant challenge that decision-makers face. Decision Support Systems that analyze data using different approaches are constantly evolving. There are many techniques that analyze these large datasets collected from Wireless Sensor Networks. Associative Classifier is one such technique which combines Associative Rule Mining along with Classification to find different patterns generated from large datasets. A common challenge associated with sensor data is that it is unstructured and heterogeneous. In this research, a Multiclass Weighted Associative Classifier with Application-based Rule Selection is proposed which translates unstructured and heterogeneous data into a set of rules that enable decision-makers in any domain to make decisions.

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Author information

Authors and Affiliations

  1. Pacific University, Udaipur, Rajasthan, India

    Disha J. Shah

  2. FCAIT, GLS University, Ahmedabad, Gujarat, India

    Disha J. Shah

  3. Department of Computer Science, Pacific University, Udaipur, Rajasthan, India

    Neetu Agarwal

Authors
  1. Disha J. Shah
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  2. Neetu Agarwal
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Corresponding author

Correspondence to Disha J. Shah .

Editor information

Editors and Affiliations

  1. Research and Industry Incubation Center, Department of Information Science and Engineering, Dayananda Sagar College of Engineering, Bangalore, India

    V. Suma

  2. Department of Technology and Maritime Innovation, University of Southeast, Horten, Norway

    Noureddine Bouhmala

  3. Go Perception Laboratory, Cornell University, Ithaca, NY, USA

    Haoxiang Wang

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Shah, D.J., Agarwal, N. (2021). Multiclass Weighted Associative Classifier with Application-Based Rule Selection for Data Gathered Using Wireless Sensor Networks. In: Suma, V., Bouhmala, N., Wang, H. (eds) Evolutionary Computing and Mobile Sustainable Networks. Lecture Notes on Data Engineering and Communications Technologies, vol 53. Springer, Singapore. https://doi.org/10.1007/978-981-15-5258-8_68

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  • DOI: https://doi.org/10.1007/978-981-15-5258-8_68

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-5257-1

  • Online ISBN: 978-981-15-5258-8

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