Update README.md
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README.md
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@@ -303,7 +303,7 @@ Function predictions are generated using `DeepFRI` across
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Generating train split: 100%|ββββββββββββ| 1332900735/1332900735 [13:11<00:00, 1684288.89 examples/s]
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Loading dataset shards: 100%|ββββββββββββββββββββββββββββββββββββββ| 219/219 [01:22<00:00, 2.66it/s]
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this loads the `>1.3B` function predictions for all 211069 targets
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The predictions are stored in long format, but can be easily converted to a wide format using pandas:
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>>> import pandas
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columns = "term_id",
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index = "id",
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values = "Y_hat")
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>>> dataset_function_prediction_wide
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## Dataset Details
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Generating train split: 100%|ββββββββββββ| 1332900735/1332900735 [13:11<00:00, 1684288.89 examples/s]
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Loading dataset shards: 100%|ββββββββββββββββββββββββββββββββββββββ| 219/219 [01:22<00:00, 2.66it/s]
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this loads the `>1.3B` function predictions for all `211069` targets across `6315` GO and EC ontology terms.
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The predictions are stored in long format, but can be easily converted to a wide format using pandas:
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>>> import pandas
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columns = "term_id",
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index = "id",
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values = "Y_hat")
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>>> dataset_function_prediction_wide.shape
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(211069, 6315)
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## Dataset Details
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