(video) Identifying Stable Periodic Frequent Patterns using SPP-Growth

Today, I present a video about finding stable periodic patterns in data, and discuss a new algorithm named SPP-Growth for this task.

VIDEO LINK: https://www.philippe-fournier-viger.com/spmf/videos/SPPGrowth.mp4

The  SPP-Growth algorithm and datasets for evaluating its performance are available in the SPMF software, which is open-source and programmed in Java.

Source code and datasets:

The source code of SPP-Growth and datasets are available in the SPMF software.

The research paper:

Fournier-Viger, P., Yang, P., Lin, J. C.-W., Kiran, U. (2019). Discovering Stable Periodic-Frequent Patterns in Transactional Data. Proc. 32nd Intern. Conf. on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA AIE 2019), Springer LNAI, pp. 230-244

If you want to watch more videos about data mining algorithms that I have recorded, you can click on the “video” category of this blog.

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Philippe Fournier-Viger is a professor, data mining researcher and the founder of the SPMF data mining software, which includes more than 150 algorithms for pattern mining.

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