PMML Compiling Predictor

This node translates a PMML model into Java scoring code and compiles it into bytecode. It then executes the code with the data from the second port. The precompilation can significantly speed up the scoring process for huge amounts of data. For small data sets the translation process might be too big of an overhead. Currently supported PMML models are all those generated by KNIME plus Naive Bayes:

  • Regression
  • SVM
  • MLP
  • K-Means Clustering
  • Decision Trees
  • Naive Bayes
  • Rulesets
  • Ensembles of the above

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 normalized class distribution
Shows the normalized class distribution for each prediction (If applicable, eg for classification models).
Suffix for probability columns
Suffix for the normalized distribution columns. Their names are like: P (trainingColumn=value).

Input Ports

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The model to be used for scoring
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The data to be scored

Output Ports

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The scored data

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