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Predict for new data. #20
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Hope it helps, |
Thanks :) Please add the same in README maybe. Might help others. |
I'm so busy atm that I can't even breathe! |
Done. #21 Will try to make changes for #7 also. Any tips on how I should approach that problem ?? I was thinking of saving the trained model in a file. and keeping the reference object inside the model object. Adding a method named predict and predicting with that model object. Doesn't seem clean, but it's a quick hack. Let me know. |
The better approach would be something supported from the original libfm repo. But I think that's not going to happen... They even removed support for the save/load model on the MCMC method. I guess we could try your approach. Just remember to correctly clean temporary files, those can be quite big when dealing with large datasets. Kudos for tackling this! |
Say I trained the model with
fm.run(train_x, train_y, val_x, val_y)
How do i run prediction for another dataset?
pred_y = fm.run(test_x)
run method expects
y_test
as input, Which doesn't make sense at all.run(self, x_train, y_train, x_test, y_test, x_validation_set=None, y_validation_set=None, meta=None)
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