You save a trained classifier with the -d option (dumping), e.g.:

 java weka.classifiers.trees.J48 -C 0.25 -M 2 -t /some/where/train.arff -d /other/place/j48.model

And you can load it with -l and use it on a test set, e.g.:

 java weka.classifiers.trees.J48 -l /other/place/j48.model -T /some/where/test.arff

Note, when loading a model you no longer need to supply specific parameters to the classifier.


A trained model can be saved like this, e.g., J48:

  • train your model on the training data /some/where/train.arff
  • right-click in the Results list on the item which model you want to save
  • select Save model and save it to /other/place/j48.model

You can load the previously saved model with the following steps:

  • load your test data /some/where/test.arff via the Supplied test set button
  • right-click in the Results list, select Load model and choose /other/place/j48.model
  • select Re-evaluate model on current test set

Based on this Weka Mailing List post.

Making Predictions with your model without retraining

See the Making predictions article for detailed information.

Source code

See Serialization for code examples.

See also