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PAttern MIning (PAMI) is a Python library containing several algorithms to discover user interest-based patterns in a wide-spectrum of datasets across multiple computing platforms. Useful links to utilize the services of this library were provided below:

1. User manual https://udaylab.github.io/PAMI/manuals/index.html

2. Coders manual https://udaylab.github.io/PAMI/codersManual/index.html

3. Code documentation https://pami-1.readthedocs.io

4. Datasets https://u-aizu.ac.jp/~udayrage/datasets.html

5. Discussions on PAMI usage https://github.com/UdayLab/PAMI/discussions

6. Report issues https://github.com/UdayLab/PAMI/issues

• ✅ Well-tested and production-ready
• 🔋 Highly optimized to our best effort, light-weight, and energy efficient
• 👀 Proper code documentation
• 🍼 Ample examples of using various algorithms at ./notebooks folder
• 🤖 Works with AI libraries such as TensorFlow, PyTorch, and sklearn.
• ⚡️ Supports Cuda and PySpark
• 🖥️ Operating System Independence
• 🔬 Knowledge discovery in static data and streams
• 🐎 Snappy
• 🐻 Ease of use

• Version 2023.07.07: New algorithms: cuApriroi, cuAprioriBit, cuEclat, cuEclatBit, gPPMiner, cuGPFMiner, FPStream, HUPMS, SHUPGrowth New codes to generate synthetic databases
• Version 2023.06.20: Fuzzy Partial Periodic, Periodic Patterns in High Utility, Code Documentation, help() function Update
• Version 2023.03.01: prefixSpan and SPADE

Total number of algorithms: 83

Installation

   pip install pami
   pip install 'pami[gpu]'
   pip install 'pami[spark]'

Updation

   pip install --upgrade pami

Uninstallation

   pip uninstall pami 

1. Frequent pattern mining: Sample

Basic	Closed	Maximal	Top-k	CUDA	pyspark
Apriori	CHARM	maxFP-growth	FAE	cudaAprioriGCT	parallelApriori
FP-growth				cudaAprioriTID	parallelFPGrowth
ECLAT				cudaEclatGCT	parallelECLAT
ECLAT-bitSet
ECLAT-diffset

2. Relative frequent pattern mining: Sample

Basic
RSFP-growth

3. Frequent pattern with multiple minimum support: Sample

Basic
CFPGrowth
CFPGrowth++

4. Correlated pattern mining: Sample

Basic
CoMine
CoMine++

5. Fault-tolerant frequent pattern mining (under development)

Basic
FTApriori
FTFPGrowth (under development)

6. Coverage pattern mining (under development)

Basic
CMine
CMine++

1. Periodic-frequent pattern mining: Sample

Basic	Closed	Maximal	Top-K
PFP-growth	CPFP	maxPF-growth	kPFPMiner
PFP-growth++		Topk-PFP
PS-growth
PFP-ECLAT
PFPM-Compliments

2. Local periodic pattern mining: Sample

Basic
LPPGrowth (under development)
LPPMBreadth (under development)
LPPMDepth (under development)

3. Partial periodic-frequent pattern mining: Sample

Basic
GPF-growth
PPF-DFS

4. Partial periodic pattern mining: Sample

Basic	Closed	Maximal	topK	CUDA
3P-growth	3P-close	max3P-growth	topK-3P growth	cuGPPMiner (under development)
3P-ECLAT				gPPMiner (under development)
G3P-Growth

5. Periodic correlated pattern mining: Sample

Basic
EPCP-growth

6. Stable periodic pattern mining: Sample

Basic	TopK
SPP-growth	TSPIN
SPP-ECLAT

7. Recurring pattern mining: Sample

Basic
RPgrowth

1. Geo-referenced frequent pattern mining: Sample

Basic
spatialECLAT
FSP-growth

2. Geo-referenced periodic frequent pattern mining: Sample

Basic
GPFPMiner
PFS-ECLAT
ST-ECLAT

3. Geo-referenced partial periodic pattern mining:Sample

Basic
STECLAT

1. High utility pattern mining: Sample

Basic
EFIM
HMiner
UPGrowth

2. High utility frequent pattern mining: Sample

Basic
HUFIM

3. High utility geo-referenced frequent pattern mining: Sample

Basic
SHUFIM

4. High utility spatial pattern mining: Sample

Basic	topk
HDSHIM	TKSHUIM
SHUIM

5. Relative High utility pattern mining: Sample

Basic
RHUIM

6. Weighted frequent pattern mining: Sample

Basic
WFIM

7. Weighted frequent regular pattern mining: Sample

Basic
WFRIMiner

8. Weighted frequent neighbourhood pattern mining: Sample

1. Fuzzy Frequent pattern mining: Sample

Basic
FFI-Miner

2. Fuzzy correlated pattern mining: Sample

Basic
FCP-growth

3. Fuzzy geo-referenced frequent pattern mining: Sample

Basic
FFSP-Miner

4. Fuzzy periodic frequent pattern mining: Sample

Basic
FPFP-Miner

5. Fuzzy geo-referenced periodic frequent pattern mining: Sample

Basic
FGPFP-Miner (under development)

1. Uncertain frequent pattern mining: Sample

Basic	top-k
PUF	TUFP
TubeP
TubeS
UVEclat

2. Uncertain periodic frequent pattern mining: Sample

Basic
UPFP-growth
UPFP-growth++

3. Uncertain Weighted frequent pattern mining: Sample

Basic
WUFIM

1. Sequence frequent pattern mining: Sample

Basic
SPADE
PrefixSpan

2. Geo-referenced Frequent Sequence Pattern mining

Basic
GFSP-Miner (under development)

1. Partial periodic pattern mining (under development)

Basic
PP-Growth (under development)

1. Frequent pattern mining

2. High utility pattern mining

1. Contiguous Frequent Patterns

Basic
PositionMining

coming soon