Automatic outlier detection for time series: an application to sensor data

  title={Automatic outlier detection for time series: an application to sensor data},
  author={Sabyasachi Basu and Martin Meckesheimer},
  journal={Knowledge and Information Systems},
In this article we consider the problem of detecting unusual values or outliers from time series data where the process by which the data are created is difficult to model. The main consideration is the fact that data closer in time are more correlated to each other than those farther apart. We propose two variations of a method that uses the median from a neighborhood of a data point and a threshold value to compare the difference between the median and the observed data value. Both variations… CONTINUE READING
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