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This software is being developed at the University of Aizu, Aizu-Wakamatsu, Fukushima, Japan

Project description

PyPI AppVeyor PyPI - Python Version GitHub all releases GitHub license PyPI - Implementation PyPI - Wheel PyPI - Status GitHub issues GitHub forks GitHub stars

Introduction

PAMI stands for PAttern MIning. It constitutes several pattern mining algorithms to discover interesting patterns in transactional/temporal/spatiotemporal databases. This software is provided under GNU GENERAL PUBLIC LICENSE Version 3, 29 June 2007.

  1. The user manual for PAMI library is available at https://udayrage.github.io/PAMI/index.html
  2. Datasets to implement PAMI algorithms are available at https://www.u-aizu.ac.jp/~udayrage/software.html
  3. Please report issues in the software at https://github.com/udayRage/PAMI/issues

Contact us by Discord https://discord.gg/9WgKkrSJ

Installation

   pip install pami

Upgrade

   pip install --upgrade pami

Details

Total available algorithms: 43

  1. Frequent pattern mining:

    Basic Closed Maximal Top-k CUDA pyspark
    Apriori Closed maxFP-growth topK cudaAprioriGCT parallelApriori
    FP-growth cudaAprioriTID parallelFPGrowth
    ECLAT cudaEclatGCT parallelECLAT
    ECLAT-bitSet
    ECLAT-diffset
  2. Frequent pattern mining using other measures:

    Basic
    RSFP
  3. Correlated pattern mining:

    Basic
    CP-growth
    CP-growth++
  4. Frequent spatial pattern mining:

    Basic
    spatialECLAT
    FSP-growth
  5. Correlated spatial pattern mining:

    Basic
    CSP-growth
  6. Fuzzy correlated pattern mining:

    Basic
    FCP-growth
  7. Fuzzy Frequent pattern mining:

    Basic
    FFI-Miner
  8. Fuzzy frequent spatial pattern mining:

    Basic
    FFSP-Miner
  9. Fuzzy periodic frequent pattern mining:

    Basic
    FPFP-Miner
  10. High utility frequent pattern mining:

    Basic
    HUFIM
  11. High utility frequent spatial pattern mining:

    Basic
    SHUFIM
  12. High utility pattern mining:

    Basic
    EFIM
    HMiner
    UPGrowth
  13. High utility spatial pattern mining:

    Basic topk
    HDSHIM TKSHUIM
    SHUIM
  14. Local periodic pattern mining:

    Basic
    LPPGrowth
    LPPMBreadth
    LPPMDepth
  15. Partial periodic frequent pattern:

    Basic
    GPF-growth
    PPF-DFS
  16. Periodic frequent pattern mining:

    Basic Closed Maximal
    PFP-growth CPFP maxPF-growth
    PFP-growth++
    PS-growth
    PFP-ECLAT
  17. Partial periodic pattern mining:

    Basic Closed Maximal topk
    3P-growth 3P-close max3P-growth Topk_3Pgrowth
    3PECLAT
  18. Periodic correlated pattern mining:

    Basic
    EPCP-growth
  19. Uncertain correlated pattern mining:

    Basic
    CFFI
  20. Uncertain frequent pattern mining:

    Basic top-k
    PUF TUFP
    TubeP
    TubeS
    UVEclat
  21. Uncertain periodic frequent pattern mining:

    Basic
    PTubeP
    PTubeS
    UPFP-growth
  22. Recurring pattern mining:

    Basic
    RPgrowth
  23. Relative High utility pattern mining:

    Basic
    RHUIM
  24. Stable periodic pattern mining:

    Basic
    SPP-growth
  25. Uncertain correlated pattern mining:

    Basic
    CFFI

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