Mining sequences with exceptional transition behaviour of varying order using quality measures based on information-theoretic scoring functions

DOI10.1007/s10618-021-00808-xOpenAlexW3215179825MaRDI QIDQ832665

Rianne M. Schouten, Marcos L. P. Bueno, Wouter Duivesteijn, Mykola Pechenizkiy

Publication date: 25 March 2022

Published in: Data Mining and Knowledge Discovery (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10618-021-00808-x

zbMATH Keywords

Markov chainsexceptional model mininginformation-theoretic scoring functionssequential medical data

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Markov processes: estimation; hidden Markov models (62M05)

Uses Software

• PrefixSpan

Cites Work

• Unnamed Item
• Estimating the dimension of a model
• Selecting the number of states in hidden Markov models: pragmatic solutions illustrated using animal movement
• Exceptional model mining. Exceptional model mining, supervised descriptive local pattern mining with complex target concepts
• MixedTrails: Bayesian hypothesis comparison on heterogeneous sequential data
• Anytime discovery of a diverse set of patterns with Monte Carlo tree search
• For real: a thorough look at numeric attributes in subgroup discovery
• Exceptional Model Mining
• Determination of the order of a Markov chain by Akaike's information criterion
• Further analysis of the data by Akaike's information criterion and the finite corrections
• Model Selection for Extended Quasi-Likelihood Models in Small Samples
• Bayes Factors
• Strictly Proper Scoring Rules, Prediction, and Estimation
• Hidden Markov Models for Time Series
• A new look at the statistical model identification

This page was built for publication: Mining sequences with exceptional transition behaviour of varying order using quality measures based on information-theoretic scoring functions