The Art and Science of Machine Intelligence : With An Innovative Application for Alzheimer’s Detection From Speech

This volume presents several machine intelligence technologies, developed over recent decades, and illustrates how they can be combined in application. One application, the detection of dementia from patterns in speech, is used throughout to illustrate these combinations. This application is a classic stationary pattern detection task, so readers may easily see how these combinations can be applied to other similar tasks. The expositions of the methods are supported by the basic theory they rest upon, and their application is clearly illustrated. The book’s goal is to allow readers to select one or more of these methods to quickly apply to their own tasks. * Includes a variety of machine intelligent technologies and illustrates how they can work together * Shows evolutionary feature subset selection combined with support vector machines and multiple classifiers combined * Includes a running case study on intelligent processing relating to Alzheimer’s / dementia detection, in addition to several applications of the machine hybrid algorithms Front Matter ....Pages i-xxii Background on Genetic Algorithms (Walker H. Land Jr., J. David Schaffer)....Pages 1-44 The Support Vector Machine (Walker H. Land Jr., J. David Schaffer)....Pages 45-76 The Generalized Regression Neural Network Oracle (Walker H. Land Jr., J. David Schaffer)....Pages 77-105 Alzheimer’s Disease and Speech Background (Walker H. Land Jr., J. David Schaffer)....Pages 107-135 Hybrid GA-SVM-Oracle Paradigm (Walker H. Land Jr., J. David Schaffer)....Pages 137-155 Classical Bayesian Theory and Networks (Walker H. Land Jr., J. David Schaffer)....Pages 157-185 Bayesian Probabilistic Neural Network (BPNN) (Walker H. Land Jr., J. David Schaffer)....Pages 187-210 Machine Intelligence Mixture of Experts and Bayesian Networks (Walker H. Land Jr., J. David Schaffer)....Pages 211-248 Quantifying Uncertainty (Walker H. Land Jr., J. David Schaffer)....Pages 249-262 Back Matter ....Pages 263-269