Titlebook: Data Science and Predictive Analytics; Biomedical and Healt Ivo D. Dinov Textbook 2023Latest edition The Editor(s) (if applicable) and The

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Linear and Nonlinear Dimensionality Reduction,corresponding simple lower-dimensional fundamental constituents. Specifically, we will discuss linear and nonlinear data dimensionality reduction techniques, such as principal and independent component analyses, factor analysis, matrix singular value decomposition, t-distributed stochastic neighbor

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Black Box Machine Learning Methods,arning methods. These techniques are applied to model market data, compute approximations of power functions, perform optical character recognition of handwritten text, and examine quality of life in chronic disease.