JMP 12 Online Documentation (English)
Discovering JMP
Using JMP
Basic Analysis
Essential Graphing
Profilers
Design of Experiments Guide
Fitting Linear Models
Specialized Models
Multivariate Methods
Quality and Process Methods
Reliability and Survival Methods
Consumer Research
Scripting Guide
JSL Syntax Reference
JMP iPad Help
JMP Interactive HTML
Capabilities Index
JMP 13.2 Online Documentation
Specialized Models
• Neural Networks
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Neural Networks
Fit Nonlinear Models Using Nodes and Layers
Most features described in this topic are for JMP Pro only and noted with this icon.
The Neural platform implements a fully connected multi-layer perceptron with one or two layers. Use neural networks to predict one or more response variables using a flexible function of the input variables. Neural networks can be very good predictors when it is not necessary to describe the functional form of the response surface, or to describe the relationship between the inputs and the response.
Example of a Neural Network
Contents
Overview of Neural Networks
Launch the Neural Platform
The Neural Launch Window
The Model Launch
Model Reports
Training and Validation Measures of Fit
Confusion Statistics
Model Options
Example of a Neural Network