From the course: SPSS: Data Visualizing and Data Wrangling

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Neural networks in SPSS: Radial basis function classification

Neural networks in SPSS: Radial basis function classification

From the course: SPSS: Data Visualizing and Data Wrangling

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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 multi-layer perceptron, which I have demonstrated elsewhere. The 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 covariates. I'm going to select the scaled ones with the measuring stick next to them and put them under covariates and then I'll take all the rest and put them into factors. And then we do have a…

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