Displays output from a multi-layer perceptron neural network fitted by NNFIT.
Option
PRINT = string tokens |
Controls fitted output (description, estimates, fittedvalues, summary); default desc, esti, summ |
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Parameter
| pointers | Save structure with details of the network and the estimated parameters |
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Description
NNDISPLAY displays results from the fit of a neural network by NNFIT. The type of neural network fitted by NNFIT is a fully-connected feed-forward multi-layer perceptron with a single hidden layer. This network starts with a row of nodes, one for each input variable (i.e. x-variate), which are all connected to every node in the hidden layer. The nodes in the hidden layer are then all connected to the output node in the final, output layer.
Details of the fit and the structure of the neural network can be supplied using the parameter of NNDISPLAY. This must have been saved using the SAVE parameter of NNFIT. If this is not set, the output is from the most recent network fitted by NNFIT.
The output is controlled by the PRINT option, with settings:
description |
a description of the network (number of input variables, nodes etc.), |
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estimates |
estimates of the free parameters, |
fittedvalues |
fitted values, |
summary |
summary (numbers of iterations, objective function etc.). |
Option: PRINT.
Parameter: unnamed.
See also
Commands for: Data mining.
Example
" Example NNDI-1: Displays output from a multi-layer perceptron neural network
fitted by NNFIT."
" This example prints the fitted values after using NNFIT to fit a multi-layer
perceptron neural network with five hidden layers, a hyperbolic activation
function in the hidden layer and a linear activation function in the output
layer."
" The data are in a file called iris.GSH and contain the data from Fisher's
Iris data set."
SPLOAD [PRINT=*] '%GENDIR%/Data/iris.GSH'
POINTER [VALUES=Sepal_Length,Sepal_Width,Petal_Length,Petal_Width] Measures
CALC yval = NEWLEVELS(Species)
NNFIT [PRINT=description,estimates,summary; NHIDDEN=5;\
HIDDENMETHOD=hyperbolictangent; OUTPUTMETHOD=linear; SEED=12]\
Y=yval; X=Measures
NNDISPLAY [PRINT = fitt]