This software is being developed at the University of Aizu, Aizu-Wakamatsu, Fukushima, Japan
Project description
PAMI stands for PAttern MIning
This software is provided under GNU GENERAL PUBLIC LICENSE Version 3, 29 June 2007. For more information on license visit: https://www.gnu.org/licenses/quick-guide-gplv3.html
PAMI constitutes of several pattern mining algorithms to discover interesting patterns in transactional/temporal/spatiotemporal databases.
Required python packages
Please install the following python packages before installing/utilizing PAMI package:
1. psutil : To calculate memory requirements of an algorithm, and
2. pandas : The patterns generated by our algorithms can be read into a pandas data frame.
As a part of future work, we intend to extend PAMI to accept pandas data frame as an input to a pattern mining algorithm.
COMMAND: pip install psutil pandas functools
User manual
The manual for working with PAMI is available at https://udayrage.github.io/PAMI/manual.html
Details
Total available algorithms: 41
-
Frequent pattern mining:
Basic Closed Maximal Top-k Apriori Closed maxFP-growth topK FP-growth ECLAT ECLAT-bitSet -
Frequent pattern mining using other measures:
Basic RSFP -
Correlated pattern mining:
Basic CP-growth CP-growth++ -
Frequent spatial pattern mining:
Basic spatialECLAT FSP-growth ? -
Correlated spatial pattern mining:
Basic SCP-growth -
Fuzzy correlated pattern mining:
Basic CFFI -
Fuzzy frequent spatial pattern mining:
Basic FFSI -
Fuzzy periodic frequent pattern mining:
Basic FPFP-Miner -
High utility frequent spatial pattern mining:
Basic HDSHUIM -
High utility pattern mining:
Basic EFIM UPGrowth -
Partial periodic frequent pattern:
Basic GPF-growth PPF-DFS -
Periodic frequent pattern mining:
Basic Closed Maximal PFP-growth CPFP maxPF-growth PFP-growth++ PS-growth PFP-ECLAT -
Partial periodic pattern mining:
Basic Maximal 3P-growth max3P-growth 3PECLAT -
Uncertain correlated pattern mining:
Basic CFFI -
Uncertain frequent pattern mining:
Basic PUF TubeP TubeS -
Uncertain periodic frequent pattern mining:
Basic PTubeP PTubeS UPFP-growth -
Local periodic pattern mining:
Basic LPPMbredth LPPMdepth LPPGrowth
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