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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…
Stewardship
SOCR Resource, University of Michigan Rights
CC-BY Credits
SOCR, MIDAS, HBBS, DCMB, University of Michigan Creation Date
August 29th, 2017
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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,…
Stewardship
SOCR Resource, University of Michigan Rights
CC-BY Credits
SOCR, MIDAS, HBBS, DCMB, University of Michigan Creation Date
July 1st, 2017
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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…
Stewardship
SOCR Resource, University of Michigan Rights
CC-BY Credits
SOCR, MIDAS, HBBS, DCMB, University of Michigan Creation Date
July 1st, 2017
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DSPA Chapter 5 Dimensionality Reduction Dimensionality reduction techniques enable exploratory data analyses
by reducing the complexity of the dataset, still approximately
preserving important…
Stewardship
SOCR Resource, University of Michigan Rights
CC-BY Credits
SOCR, MIDAS, HBBS, DCMB, University of Michigan Creation Date
August 1st, 2017
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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…
Stewardship
SOCR Resource, University of Michigan Rights
CC-BY Credits
SOCR, MIDAS, HBBS, DCMB, University of Michigan Creation Date
August 1st, 2017
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