experimentation
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Currently you can only do training when you've committed and pushed all new changes in your branch. This introduces a blocker when a Data Scientist is trying out lots of different changes in their code.
Allow for training even with uncommitted changes. This can be done by taking a git diff of the current branch, storing it and then doing an git apply to the current branch during training
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The STMC1, STMC2, and REG axioms depend on similarities. It might be promising to have similarity variants that are based on word embeddings fine-tuned on test collections like Robust 04.
It is only required to have some word embeddings that PyMagnitude can handle, the rest is already implemented.
To implement new embedding variants, take a look at the fastText implementation here:
https://gi
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When we show data for a metric, we currently don't include the current day's worth of data. For users just getting set up, they may only have events from today, and want to test out if the query is working, and by excluding events from 'today', they can't see results.
TODO:
packages/back-end/src/services/experiments.tson line329, instead of using the current date as the value