What it can do for your business

IBM SPSS Neural Networks uses nonlinear data modeling to discover complex relationships and derive greater value from your data. Take advantage of multilayer perceptron (MLP) or radial basis function (RBF) procedures. You can set the conditions—control the training stopping rules and network architecture—or let the procedure choose. Influence the weighting of variables, and specify details of the network architecture. Select the type of model training, and share results using graphs and charts.

This module is included in the SPSS Premium package. Available at an additional cost for the Base, Standard and Professional packages.

Uncover relationships

Choose MLP for finding more relationships or RBF for speed—both operate on a training set of data and then apply that knowledge to the entire data set and to any new data.

Control the process

Specify dependent variables—scale, categorical or a combination. Adjust by choosing how to partition the data set, which architecture and what computation resources to apply.

Improve insight

Combine with other statistical procedures or techniques and confirm results with traditional statistical techniques using IBM SPSS Statistics Base.

Product images

Multilayer Perceptron variable selection
Multilayer Perceptron variable selection
Multilayer Perceptron Partition settings
Multilayer Perceptron Partition settings
Multilayer Perceptron output settings
Multilayer Perceptron output settings

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