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## Discovering and Predicting Patterns Using Neural Network Models

See how to:

• Understand a neural network as a function of a set of derived inputs, called hidden nodes, that are nonlinear functions of the original inputs
• Interpret Neural Network diagram inputs (factors) and outputs (responses)
• Understand terms and how they apply to building Neural Networks (nodes, activation type, activation functions)
• Understand types of activation functions  (TanH, Linear, Gaussian, Sigmoid, Identity and Radial) that transform a linear combination of the X variables at the nodes of hidden layers
• Follow sequence for building a Neural Network model
• Launch model (JMP vs. JMP Pro)
• Specify # nodes in first and second layer
• Use boosting to build a larger additive model fit on the scaled residuals of previous smaller models)
• Specify Learning Rate (closer to 1 will run model faster, but may tend to overfit)
• Transform covariates
• Use Robust Fit for continuous output to minimize impact of outliers
• Understand how JMP uses penalty methods and number of tours
• Select Penalty Method (Squared, Absolute, No Penalty) to help avoid overfitting
• Select number of Tours
• Case study building a neural network for a continuous response
• Use JMP validation to avoid overfitting
• Compare Training set and Validation set values
• Use Model Launch to change Neural Net settings
• Use Actual by Predicted Plot and Profiler to evaluate how predictors impact results
• Save formulas, publish Prediction Formula for Model Comparison
• Save Fast Formulas and examine them in data table
• Save to Formula Depot for comparison with other model results
• Case study building a neural network for categorical response
• Interpret Fit Statistics, Confusion Matrix, ROC Curves and Lift Curves
• Understand why Transformation and Robust Fit options don't apply to categorical responses

Note: Q&A included at times 18:59, 19:49, 20:51 and 44:10.

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### Use Videos and Resources to Practice JMP, JMP Pro, JMP Clinical and JMP Genomics.

1-hour live Mastering JMP webinars occur most Fridays from January through October. After each session, we hope you will use the video and resources shared by the presenting JMP Systems Engineers to practice what you saw.

Mastering JMP Videos are available here.