multilayerperceptronnode properties
Multilayer perceptron is a
classifier based on the feedforward artificial neural network and consists of multiple layers. Each
layer is fully connected to the next layer in the network. The MultiLayerPerceptron-AS node in SPSS
Modeler is implemented in Spark. For details about the multilayer perceptron classifier (MLPC), see
https://spark.apache.org/docs/latest/ml-classification-regression.html#multilayer-perceptron-classifier.
multilayerperceptronnode properties |
Data type | Property description |
|---|---|---|
custom_fields |
boolean | This option tells the node to use field information specified here instead of that given in any upstream Type node(s). After selecting this option, specify the following fields as required. |
target |
field | One field name for target. |
inputs |
field | List of the field names for input. |
num_hidden_layers
|
string | Specify the number of hidden layers. Use a comma between multiple hidden layers. |
num_output_number
|
string | Specify the number of output layers. |
random_seed
|
integer | Generate the seed used by the random number generator. |
maxiter |
integer | Specify the maximum number of iterations to perform. |
set_expert |
boolean | Select the Expert Mode option in the Model Building section if you want to specify the block size for stacking input data in matrices. |
block_size |
integer | This option can speed up the computation. |
use_model_name |
boolean | Specify a custom name for the model or use auto, which sets the label as the
target field. |
model_name |
string | Renamed model name. |