# Scoring and sorting all samples during textcat teach

**URL:** <https://support.prodi.gy/t/scoring-and-sorting-all-samples-during-textcat-teach/3591>\
**Category:** Uncategorized\
**Tags:** usage, textcat\
**Created:** [October 30, 2020, 8:51pm UTC](https://support.prodi.gy/t/scoring-and-sorting-all-samples-during-textcat-teach/3591 "2020-10-30T20:51:53Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![atakanokan](https://avatars.discourse-cdn.com/v4/letter/a/e8c25b/32.png) [@atakanokan](https://support.prodi.gy/u/atakanokan)\
**Post date:** [October 30, 2020, 8:51pm UTC](https://support.prodi.gy/t/scoring-and-sorting-all-samples-during-textcat-teach/3591/1 "2020-10-30T20:51:53Z")

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Hi,

I have been trying to understand how the active-learning is working under a `teach` recipe, specifically for the text classification case: `textcat.teach`. Couple of questions around it:

1. Does the line ` stream = prefer_uncertain(model(stream))` (located at [https://github.com/explosion/prodigy-recipes/blob/0037b32d954e0b1672f9dae1e8aa53ac0c9136e3/textcat/textcat\_custom\_model.py#L63](https://github.com/explosion/prodigy-recipes/blob/0037b32d954e0b1672f9dae1e8aa53ac0c9136e3/textcat/textcat_custom_model.py#L63)) score and resort **ALL** samples in an input file (e.g. JSONL)? Or does it score and resort only `batch_size` number of samples from the already annotated samples?
2. For a highly imbalanced dataset (major class being 0 in a binary classification task), is it better to use `prefer_high_scores` instead of `prefer_uncertain` to construct a more balanced dataset?

Thanks!

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**Author:** ![ines](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/ines/32/3_2.png) [@ines](https://support.prodi.gy/u/ines)\
**Post date:** [November 2, 2020, 9:16am UTC](https://support.prodi.gy/t/scoring-and-sorting-all-samples-during-textcat-teach/3591/2 "2020-11-02T09:16:46Z")

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A post was merged into an existing topic: [Prodigy Active Learning prefer\_uncertain mechanism](https://support.prodi.gy/t/prodigy-active-learning-prefer-uncertain-mechanism/657)

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**Author:** ![ines](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/ines/32/3_2.png) [@ines](https://support.prodi.gy/u/ines)\
**Post date:** [November 2, 2020, 9:16am UTC](https://support.prodi.gy/t/scoring-and-sorting-all-samples-during-textcat-teach/3591/3 "2020-11-02T09:16:46Z")

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