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Amna Al-Sayed, Mashael M. Khayyat and Nuha Zamzami
Different data types are frequently included in clinical data. Applying machine learning algorithms to mixed data can be difficult and impact the output accuracy and quality. This paper proposes a hybrid model of unsupervised and supervised learning tech...
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Thomas Lartigue, Stanley Durrleman and Stéphanie Allassonnière
The Expectation Maximisation (EM) algorithm is widely used to optimise non-convex likelihood functions with latent variables. Many authors modified its simple design to fit more specific situations. For instance, the Expectation (E) step has been replace...
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Andrea Ruggieri, Francesco Stranieri, Fabio Stella and Marco Scutari
Incomplete data are a common feature in many domains, from clinical trials to industrial applications. Bayesian networks (BNs) are often used in these domains because of their graphical and causal interpretations. BN parameter learning from incomplete da...
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Edesiri Nkemnole
AbstractThe movement of stock prices, in capital markets across the world, has been found to be both random and non-random. Basically, for a stock price to follow a random walk, its future price changes randomly based on all currently available informati...
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