This chapter introduces decision-making using a Hidden Markov model (HMM). Specifically, it focuses on the Gaussian Mixture model, which is an unsupervised machine learning Hidden Markov model used with time-series data. The beauty of this model is its lack of sensitivity to non-stationary data. After reading this chapter, you will better understand how the Gaussian Mixture model works and will know how to develop one. Note that HMM is an unsupervised learner, which means ...
© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2022
T. C. NokeriEconometrics and Data Sciencehttps://doi.org/10.1007/978-1-4842-7434-7_66. Finding Hidden Patterns in World Economy and Growth
Tshepo Chris Nokeri1
(1)
Pretoria, South Africa
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