Biomaterial Database

Assessment of neural network models using prediction analysis. 1995

J F Thayer, and A von Eye, and M J Rovine

Department of Psychology, University of Missouri, Columbia 65211, USA.

Examination of classification or confusion matrices in neural network models is often advocated as a way to investigate the effects of network architecture on classification rules and to understand the topography of the classification space. In addition, for model comparison purposes it is useful to be able to make statements concerning the statistical reliability of these patterns of hit and error cells. Prediction analysis provides a number of descriptive and inferential measures for the evaluation of hypotheses about patterns of hit and error cells. The present paper applied recent advances in prediction analysis to the examination of neural network classification matrices. Results of the application of prediction analysis to the generalized XOR problem and to data from classification of cardiovascular responses of human subjects were used to illustrate the determination of absolute and relative fit of omnibus models as well as the evaluation of specific hypotheses within these models.

UI	MeSH Term	Description	Entries
D010698	Phobic Disorders	Anxiety disorders in which the essential feature is persistent and irrational fear of a specific object, activity, or situation that the individual feels compelled to avoid. The individual recognizes the fear as excessive or unreasonable.	Claustrophobia,Neuroses, Phobic,Phobia, School,Phobias,Phobic Neuroses,Scolionophobia,Disorder, Phobic,Phobia,Phobic Disorder,School Phobia
D002319	Cardiovascular System	The HEART and the BLOOD VESSELS by which BLOOD is pumped and circulated through the body.	Circulatory System,Cardiovascular Systems,Circulatory Systems
D002965	Classification	The systematic arrangement of entities in any field into categories classes based on common characteristics such as properties, morphology, subject matter, etc.	Systematics,Taxonomy,Classifications,Taxonomies
D005069	Evaluation Studies as Topic	Works about studies that determine the effectiveness or value of processes, personnel, and equipment, or the material on conducting such studies.	Critique,Evaluation Indexes,Evaluation Methodology,Evaluation Report,Evaluation Research,Methodology, Evaluation,Pre-Post Tests,Qualitative Evaluation,Quantitative Evaluation,Theoretical Effectiveness,Use-Effectiveness,Critiques,Effectiveness, Theoretical,Evaluation Methodologies,Evaluation Reports,Evaluation, Qualitative,Evaluation, Quantitative,Evaluations, Qualitative,Evaluations, Quantitative,Indexes, Evaluation,Methodologies, Evaluation,Pre Post Tests,Pre-Post Test,Qualitative Evaluations,Quantitative Evaluations,Report, Evaluation,Reports, Evaluation,Research, Evaluation,Test, Pre-Post,Tests, Pre-Post,Use Effectiveness
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D016002	Discriminant Analysis	A statistical analytic technique used with discrete dependent variables, concerned with separating sets of observed values and allocating new values. It is sometimes used instead of regression analysis.	Analyses, Discriminant,Analysis, Discriminant,Discriminant Analyses
D016571	Neural Networks, Computer	A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming.	Computational Neural Networks,Connectionist Models,Models, Neural Network,Neural Network Models,Neural Networks (Computer),Perceptrons,Computational Neural Network,Computer Neural Network,Computer Neural Networks,Connectionist Model,Model, Connectionist,Model, Neural Network,Models, Connectionist,Network Model, Neural,Network Models, Neural,Network, Computational Neural,Network, Computer Neural,Network, Neural (Computer),Networks, Computational Neural,Networks, Computer Neural,Networks, Neural (Computer),Neural Network (Computer),Neural Network Model,Neural Network, Computational,Neural Network, Computer,Neural Networks, Computational,Perceptron
D016584	Panic Disorder	A type of anxiety disorder characterized by unexpected panic attacks that last minutes or, rarely, hours. Panic attacks begin with intense apprehension, fear or terror and, often, a feeling of impending doom. Symptoms experienced during a panic attack include dyspnea or sensations of being smothered; dizziness, loss of balance or faintness; choking sensations; palpitations or accelerated heart rate; shakiness; sweating; nausea or other form of abdominal distress; depersonalization or derealization; paresthesias; hot flashes or chills; chest discomfort or pain; fear of dying and fear of not being in control of oneself or going crazy. Agoraphobia may also develop. Similar to other anxiety disorders, it may be inherited as an autosomal dominant trait.	Panic Attacks,Attack, Panic,Attacks, Panic,Disorder, Panic,Disorders, Panic,Panic Attack,Panic Disorders