NEW: SPSS Neural Network
With this release, SPSS Inc. introduces a new module to the SPSS Family. SPSS Neural Networks 16.0 provides a complementary approach to the statistical techniques available in SPSS Base and other add-on modules. From
the familiar SPSS interface, use SPSS Neural Networks to mine data and discover more complex relationships than is possible using more traditional, linear statistical techniques.
Neural networks are non-linear statistical data mining tools that consist of input and output layers plus one or more hidden layers of unobservable nodes. In a neural network, the connections between neurons have
weights associated with them. By adjusting the connection weights during training to match predictions to target variables or specific records, the network "learns" to generate better and better predictions.
In an MLP network like the one shown here, the data feeds forward from the input layer through one or more hidden layers to the output layer. Click graphic above to enlarge.
With the SPSS Neural Networks module, you can choose either the Multilayer Perceptron (MLP) or Radial Basis Function (RBF) procedure to explore your data.
Back to New Features page.
Back to SPSS Add-on Modules page.
Back to SPSS software main page.
|
