In accordance with the MALLET documentation , it is possible to gradually train models on topics:
"- output-model [FILENAME] This parameter specifies the file to write the serialized object of the topic trainers. This type of output is suitable for pausing and resuming training."
I would like to train topics in one dataset and then grow the model with another dataset. After both stages of training, I would like to display states for both datasets (with --output-state). Here is how I am trying to do this:
../mallet-2.0.7/bin/mallet import-dir --input input/ --keep-sequence --output input.mallet
../mallet-2.0.7/bin/mallet train-topics --input input.mallet --num-topics 3 --output-state topic-state.gz --output-model model
../mallet-2.0.7/bin/mallet import-dir --input input2/ --keep-sequence --output input2.mallet --use-pipe-from input.mallet
../mallet-2.0.7/bin/mallet train-topics --input input2.mallet --num-topics 3 --num-iterations 100 --output-state topic-state2.gz --input-model model
In the last command, if I add an βinput model modelβ, the data from the second data set is not in the output state file. If I do not add it, the data from the first data set is not in the output state file.
If I try to add additional instances to the model in code:
model.addInstances(instances);
model.setNumThreads(2);
model.setNumIterations(50);
model.estimate();
[...]
model.addInstances(instances2);
model.setNumThreads(2);
model.setNumIterations(50);
model.estimate();
I get an error message:
Exception in thread "main" java.lang.ArrayIndexOutOfBoundsException: 30
at cc.mallet.topics.ParallelTopicModel.buildInitialTypeTopicCounts(ParallelTopicModel.java:364)
at cc.mallet.topics.ParallelTopicModel.addInstances(ParallelTopicModel.java:276)
at cc.mallet.examples.TopicModel2.main(TopicModel2.java:66)
Previously, there were similar questions on the MALLET list: http://permalink.gmane.org/gmane.comp.ai.mallet.devel/924 , http://permalink.gmane.org/gmane.comp.ai.mallet.devel/ 2139
So, is it possible to gradually train thematic models?
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