From the course: SPSS Statistics Essential Training (2019)

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Neural networks in SPSS: Radial basis function classification

Neural networks in SPSS: Radial basis function classification - SPSS Tutorial

From the course: SPSS Statistics Essential Training (2019)

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Neural networks in SPSS: Radial basis function classification

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- [Instructor] Neural networks are a new arrival to SPSS and it gives you the choice of two options that have been in use for several years. One is the multilayer perceptron, which I have demonstrated elsewhere. There other one is the radial basis function, or RBF. And the idea here is that you're going to build a model that predicts an outcome using the provided data as an input layer and then one or more hidden layers, which are intermediary calculations, on the way to creating a model for the final outcome or classification. To do this, let's go to Neural Networks and Radial Basis Function. Now, what we need to do is pick our outcome variable. I'm going to use the same variable I've used in other examples, that's the pager, and then we take our predictors and put them into factors and co-variates. I'm going to select the scaled ones with the measurements taken next to them and put them under Co-variates and then I'll…

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