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Data-based Predictive Modeling                     by supervised Machine learning

Database of solved examples (input-output)

Preparation: cleanup, transform, add new attributes...

Split data into a training and a test set

Training:

Develop model on the training set

Evaluation:

  See how the model fares on the test set

Actual use:

  Use successful model on new input data to estimate unknown output

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