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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

Code documentation

Link

Details

Total available algorithms: 70

Click on "Basic" link to view the basic tutorial on using the algorithm. Similarly, click on "Adv" link to view the advanced tutorial on using a particular algorithm.

  1. Frequent pattern mining: Sample
Basic Closed Maximal Top-k CUDA pyspark
Apriori Basic-Adv Closed Basic-Adv maxFP-growth Basic topK Basic-Adv cudaAprioriGCT parallelApriori Basic-Adv
FP-growth Basic-Adv cudaAprioriTID parallelFPGrowth Basic-Adv
ECLAT Basic-Adv cudaEclatGCT parallelECLAT Basic-Adv
ECLAT-bitSet Basic-Adv
ECLAT-diffset
  1. Relative Frequent Patterns: Sample
Basic
RSFP Basic-Adv
  1. Frequent pattern with multiple minimum support: Sample
Basic
CFPGrowth
CFPGrowth++
  1. Correlated pattern mining: Sample
Basic
CP-growth Basic -Adv
CP-growth++ Basic -Adv
  1. Frequent spatial pattern mining: Sample
Basic
spatialECLAT Basic-Adv
FSP-growth Basic-Adv
  1. Fuzzy Frequent pattern mining: Sample
Basic
FFI-Miner Basic-Adv
  1. Fuzzy correlated pattern mining: Sample
Basic
FCP-growth Basic-Adv
  1. Fuzzy frequent spatial pattern mining: Sample
Basic
FFSP-Miner Basic-Adv
  1. Fuzzy periodic frequent pattern mining: Sample
Basic
FPFP-Miner Basic-Adv
  1. Geo referenced Fuzzy periodic frequent pattern mining:
Basic
FPFP-Miner Basic-Adv
  1. High utility pattern mining: Sample
Basic
EFIM Basic-Adv
HMiner Basic-Adv
UPGrowth
  1. High utility frequent pattern mining: Sample
Basic
HUFIM
  1. High utility frequent spatial pattern mining: Sample
Basic
SHUFIM
  1. High utility spatial pattern mining: Sample
Basic topk
HDSHIM TKSHUIM
SHUIM
  1. Periodic frequent pattern mining: Sample
Basic Closed Maximal
PFP-growth Basic-Adv CPFP Basic-Adv maxPF-growth Basic
PFP-growth++ Basic-Adv
PS-growth Basic-Adv
PFP-ECLAT Basic-Adv
  1. Geo referenced Periodic frequent pattern mining: Sample
Basic
GPFPMiner Basic-Adv
  1. Local periodic pattern mining: Sample
Basic
LPPGrowth
LPPMBreadth
LPPMDepth
  1. Partial periodic frequent pattern mining: Sample
Basic
GPF-growth Basic-Adv
PPF-DFS Basic-Adv
  1. Partial periodic pattern mining: Sample
Basic Closed Maximal topk
3P-growth Basic-Adv 3P-close Basic-Adv max3P-growth Basic Topk_3Pgrowth
3PECLAT Basic-Adv
  1. Partial periodic spatial pattern mining:Sample
Basic
STECLAT Basic-Adv
  1. Periodic correlated pattern mining: Sample
Basic
EPCP-growth Basic-Adv
  1. Stable periodic pattern mining: Sample
Basic
SPP-growth Basic-Adv
SPP-ECLAT Basic-Adv
  1. Uncertain frequent pattern mining: Sample
Basic top-k
PUF Basic-Adv TUFP
TubeP
TubeS
UVEclat
  1. Uncertain periodic frequent pattern mining: Sample
Basic
UPFP-growth
  1. Recurring pattern mining: Sample
Basic
RPgrowth
  1. Relative High utility pattern mining: Sample
Basic
RHUIM
  1. Weighted frequent pattern mining: Sample
Basic
WFIM Basic-Adv
  1. Uncertain Weighted frequent pattern mining: Sample
Basic
WUFIM
  1. Weighted frequent regular pattern mining: Sample
Basic
WFRIMiner
  1. Weighted frequent neighbourhood pattern mining: TO BE WRITTEN
Basic
SSWFPGrowth

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