Enhanced Bayesian Gaussian hidden Markov mixture clustering for improved knowledge discovery

• Published in: Pattern analysis and applications : PAA Vol. 27; no. 4
• Main Authors: Ganesan, Anusha, Paul, Anand, Kim, Sungho
• Format: Journal Article
• Language: English
• Published: London Springer London 01.12.2024; Springer Nature B.V
• Subjects: Anomalies; Bayesian analysis; Clustering; Computer Science; Computing time; Data mining; Datasets; Gaussian process; Knowledge discovery; Markov chains; Natural language processing; Original Article; Pattern Recognition; Prediction models; Probabilistic models; Sequences; Speech recognition; Viterbi algorithm; Cross-validation; Bayesian; Distance metric; Mixture models; Bayesian Gaussian mixture model; Hidden Markov model; Gaussian; Baum–Welch algorithm; Clustering

The hidden Markov model (HMM) is widely utilized in natural language processing, speech recognition, autonomous vehicular systems, and healthcare for tasks such as clustering, pattern recognition, predictive modeling, anomaly detection, and time-series forecasting. However, HMMs can be sensitive to...