This book offers a comprehensive framework for mastering the complexities of learning high-dimensional sparse graphical models through the use of conditional independence tests. These tests are ...

Bayesian model selection offers a coherent framework for identifying the most plausible models when the number of candidate predictors greatly exceeds the number of observations. Central to this ...

Unfortunately, this book can't be printed from the OpenBook. If you need to print pages from this book, we recommend downloading it as a PDF. Visit NAP.edu/10766 to get more information about this ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...

Data modeling best practices help define a formal process that gives structure and direction to an organization’s data. Read more about data modeling now. Data modeling, at its core, is the process of ...