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
Explaining Differences in Classes of Discrete Sequences
Data Mining Template Library
PRISM Algorithm for frequent sequence mining using the block-encoding approach
SPADE frequent sequence mining algorithm
VOGUE: Variable Order HMM with Duration
Solutions to data mining course homeworks.
Utils for itemset and sequence mining
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
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.
WINEPI Episode Mining algorithm for R based on Python implementation by duytri and nkmrtty
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