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

Installation

   pip install pami

Upgrade

   pip install --upgrade pami

Details

Total available algorithms: 43

1. Frequent pattern mining:

   Basic	Closed	Maximal	Top-k
   Apriori	Closed	maxFP-growth	topK
   FP-growth
   ECLAT
   ECLAT-bitSet

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
   SCP-growth

6. Fuzzy correlated pattern mining:

   Basic
   CFFI

7. Fuzzy frequent spatial pattern mining:

   Basic
   FFSI

8. Fuzzy periodic frequent pattern mining:

   Basic
   FPFP-Miner

9. High utility frequent spatial pattern mining:

   Basic
   HDSHUIM

10. High utility pattern mining:

    Basic
    EFIM
    UPGrowth

11. Partial periodic frequent pattern:

    Basic
    GPF-growth
    PPF-DFS

12. Periodic frequent pattern mining:

    Basic	Closed	Maximal
    PFP-growth	CPFP	maxPF-growth
    PFP-growth++
    PS-growth
    PFP-ECLAT

13. Partial periodic pattern mining:

    Basic	Maximal
    3P-growth	max3P-growth
    3PECLAT

14. Uncertain correlated pattern mining:

    Basic
    CFFI

15. Uncertain frequent pattern mining:

    Basic
    PUF
    TubeP
    TubeS

16. Uncertain periodic frequent pattern mining:

    Basic
    PTubeP
    PTubeS
    UPFP-growth

17. Local periodic pattern mining:

    Basic
    LPPMbredth
    LPPMdepth
    LPPGrowth

18. Recurring pattern mining:

    Basic
    RPgrowth