PAMI is a Python library containing 100+ algorithms to discover useful patterns in various databases across multiple computing platforms. (Active)

• UpdatedJul 3, 2025
• Jupyter Notebook

Association Rule Mining from Spatial Data for Crime Analysis

• UpdatedFeb 7, 2019
• Jupyter Notebook

GSP (Generalized Sequence Pattern) algorithm in Python

• UpdatedOct 27, 2025
• Python

IBM Synthetic Data Generator for Itemsets and Sequences

• UpdatedDec 22, 2019
• C++

Disease Pattern Miner is a free, open-source mining framework for interactively discovering sequential disease patterns in medical health record datasets.

• UpdatedMar 21, 2019
• Java

cSPADE: mining frequent sequence patterns with constraints (extension of SPADE)

• UpdatedJul 15, 2020
• C++

This repo is created to perform I/O Request Packet (IRP) driven ransomware analysis where the IRP logs were collected during ransomware execution.

• UpdatedAug 14, 2020
• Python

Some code and data on demographic sequences

• UpdatedJan 13, 2017
• Python

Explaining Differences in Classes of Discrete Sequences

• UpdatedJun 5, 2020
• Python

Data Mining Template Library

• UpdatedJan 5, 2022
• C++

PRISM Algorithm for frequent sequence mining using the block-encoding approach

• UpdatedMar 28, 2020
• C++

SPADE frequent sequence mining algorithm

• UpdatedMar 28, 2020
• C++

VOGUE: Variable Order HMM with Duration

• UpdatedMar 29, 2020
• Python

Solutions to data mining course homeworks.

• UpdatedAug 19, 2021
• Jupyter Notebook

• UpdatedFeb 21, 2017
• Jupyter Notebook

Utils for itemset and sequence mining

• UpdatedMar 28, 2020
• C++

Suffix Tree based method to find repeated sequences

• UpdatedMar 15, 2018

Data Generation and Figure Construction to Describe Teaching Analytics and Provide Insight into Their Importance in the Evolution of Educational Methods.

• UpdatedFeb 6, 2024
• HTML

Pattern mining finds useful patterns for decision-making and prediction, especially in sequence mining. It is widely applied in retail, healthcare, and security, including medical data analysis. Analyzing US health data (2013–2017) helps identify mortality-related patterns. The PrefixSpan algorithm extracts sequential patterns from this dataset.

• UpdatedJan 30, 2025
• Java

WINEPI Episode Mining algorithm for R based on Python implementation by duytri and nkmrtty

• UpdatedApr 3, 2023
• R