MultiLayerPerceptron Predictor

Based on a trained MultiLayerPerceptron-model given at the model inport of this node, the expected output values are computed. If the output variable is nominal, the output of each neuron and the class of the winner neuron are produced. Otherwise, the regression value is computed. Filter out missing values before using this node.

Options

Change prediction column name
When set, you can change the name of the prediction column.
Prediction Column
The possibly overridden column name for the predicted column. (The default is: Prediction ( trainingColumn ) .)
Append columns with class probabilities
When classification is done and this option is set, the class probabilities are appended.
Note that the probabilities for the different classes are calculated independently i.e. if your classification problem has n classes, then the MLP treats it as n binary classification problems.
Suffix for probability columns
Suffix for the probability columns. Their names are like: P ( trainingColumn = value ) .

Input Ports

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Trained MLP Neural Network
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Datatable with test data to classify

Output Ports

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Datatable with classified data

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