File-based Prediction Structure

A File-based Prediction Structure is a prediction structure that is a file-based data structure.

• Context:
  • It can assume a Feature Data Preparation Task.
  • …
• Example(s):
  • a scikit-learn Model File.
  • a PMML-based Decision Tree Model File.
  • …
• Counter-Example(s):
  • a Memory-based Prediction Structure.
  • a File-based Tabular Data Structure.
• See: PMML, PMML File.

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References

2014

• http://scikit-learn.org/stable/modules/model_persistence.html#model-persistence
  • After training a scikit-learn model, it is desirable to have a way to persist the model for future use without having to retrain. The following section gives you an example of how to persist a model with pickle. We’ll also review a few security and maintainability issues when working with pickle serialization. …

    … It is possible to save a model in the scikit by using Python’s built-in persistence model, namely pickle:

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