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` |
---|

### Parameter

pointers |
Save structure with details of the network and the estimated parameters |
---|

### 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.), |
---|---|

`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]