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

Association Rule Mining from Spatial Data for Crime Analysis

GSP (Generalized Sequence Pattern) algorithm in Python

IBM Synthetic Data Generator for Itemsets and Sequences

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

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

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

Some code and data on demographic sequences

Data Mining Template Library

Explaining Differences in Classes of Discrete Sequences

SPADE frequent sequence mining algorithm

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

VOGUE: Variable Order HMM with Duration

Solutions to data mining course homeworks.

Utils for itemset and sequence mining

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.

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

Suffix Tree based method to find repeated sequences