Mining Recurrent Concepts in Data Streams Using the Discrete Fourier Transform

  title={Mining Recurrent Concepts in Data Streams Using the Discrete Fourier Transform},
  author={Sripirakas Sakthithasan and R. Pears},
In this research we address the problem of capturing recurring concepts in a data stream environment. Recurrence capture enables the re-use of previously learned classifiers without the need for re-learning while providing for better accuracy during the concept recurrence interval. We capture concepts by applying the Discrete Fourier Transform (DFT) to Decision Tree classifiers to obtain highly compressed versions of the trees at concept drift points in the stream and store such trees in a… Expand
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  • S. Ramamurthy, R. Bhatnagar
  • Computer Science
  • Sixth International Conference on Machine Learning and Applications (ICMLA 2007)
  • 2007
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