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multilayerperceptronnode properties
multilayerperceptronnode properties
Last updated: Feb 12, 2025
multilayerperceptronnode properties

MultiLayerPerceptron-AS node iconMultilayer 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.

Table 1. multilayerperceptronnode properties
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.