A data-oriented approach for outlier detection

https://doi.org/10.18535/ijsrm/v7i1.ec01
Data characteristics, Nominal attribute, outlier analysis, machine learning, model verification

Authors

  • Nripesh Trivedi Department of mathematical sciences. Indian Institute of Technology, Varanasi, India, India
Vol. 7 No. 01 (2019)
Engineering and Computer Science
January 16, 2019

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In this paper, characteristics of data obtained from the sensors (used in OpenSense project) are identified in order to build a data-oriented approach. This approach consists of application of Class Outliers: Distance Based (CODB) and Hoeffding tree algorithms. Subsequently, machine learning models were built to detect outliers in a sensor data stream. The approach presented in this paper may be used for developing methodologies for data-oriented outlier detection