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DSPA Chapter 20 Prediction and Internal Statistical Cross-validation

Chapter 20 uses Google Flu Trends, Autism, and Parkinson’s disease case-studies to illustrate (1) alternative forecasting types using linear and non-linear predictions, (2) exhaustive and…

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DSPA Chapter 18 Big Longitudinal Data Analysis (Timeseries GEE GLMM SEM)

DSPA Chapter 18 Big Longitudinal Data Analysis (Timeseries GEE GLMM SEM)The time-varying (longitudinal) characteristics of large information flows represent a special case of the complexity, dynamic…

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DSPA Chapter 17 (Regularized Linear Modeling and Controlled Variable Selection)

DSPA Chapter 17 (Regularized Linear Modeling and Controlled Variable Selection) Classical techniques for choosing important covariates to include in a model of complex multivariate data relied on…

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DSPA Chapter 5 Dimensionality Reduction

DSPA Chapter 5 Dimensionality Reduction Dimensionality reduction techniques enable exploratory data analyses by reducing the complexity of the dataset, still approximately preserving important…

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DSPA Chapter 7 Naive Bayes Classification

DSPA Chapter 7 Naive Bayes Classification Please review the introduction to Chapter 6, where we described the types of machine learning methods and presented lazy classification for numerical…

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