Classification & Anomaly detection

  • LCIF: Combining Instance and Feature neighbors for Efficient Multi-label Classification (by Len Feremans)
  • PBAD: Pattern-Based Anomaly Detection in Mixed-Type Time Series (by Len Feremans)
  • TIPM: Interactive time series pattern mining and anomaly detection in multi-dimensional time series and event logs (by Len Feremans)
  • EDBN: Extended Dynamic Bayesian Networks (by Stephen Pauwels)
  • ACD2: A tool for detecting anomalies and concept drifts in business process logs (by Stephen Pauwels)

Data Quality Rules

  • CFD Discovery Algorithms: Implementations for discovering frequent, approximate Conditional Functional Dependencies from csv data (by Joeri Rammelaere)
  • XPlode: The XPlode algorithm discovers a Conditional Functional Dependency based on a given partial repair of a dataset. The returned CFD provides the best explanation for the observed repair (by Joeri Rammelaere)
  • FBIMiner: Forbidden Itemsets are itemsets with a low lift, aiming to capture anomalous co-occurences in data, which in practice are often erroneous. The program further attempts to repair the data, in order to remove all forbidden itemsets (by Joeri Rammelaere)
  • CTane and CFDMiner: Implementations of the CTane and CFDMiner algorithms for discovering Conditional Functional Dependencies.

Databases & Query languages

  • Blixem: A LiXQuery engine (by Jeroen Avonts, Pieter Wellens, Wim Le Page)
  • Conqueror: Conjunctive Query Generator (by Wim Le Page)

Frequent Pattern Mining

Interactive & Efficient Pattern Mining

Pattern mining on sequential data & Interestingness measures

  • FCI seq: Efficient Discovery of Sets of Co-occurring Items in Event Sequences (by Len Feremans)
  • FCI extended: Efficiently Mining Cohesion-based Patterns and Rules in Event Sequences (by Len Feremans)
  • Mining Closed Strict Episodes and Marbles (by Nikolaj Tatti)
  • SCII: Sequence Classification based on Interesting Itemsets (by Cheng Zhou)
  • SQS: The Long and the Short of It: Summarizing Event Sequences with Serial Episodes (by Nikolaj Tatti, Jilles Vreeken)
  • QCSP: Mining Top-k Quantile-based Cohesive Sequential Patterns (by Len Feremans)

Pattern sets & Summarisation