Comments (3)
@zilto Closing this because the API, including the code snippet, has changed. We will also try to add some end-to-end examples soon!
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@zilto Thanks for flagging! Good catch.
I don't know the motivations behind separating
Recipe
,RecipeTransform
, andTransformResult
. What raises questions is that both thetransform
and thetrain_fitted
objects need to accesstrain
, but only the latter has.features
and.outcomes
set. Users coming from scikit-learn would expect 2 "layers" instead of 3 withRecipe
(with afitted: bool
flag) and some sort of result.
I don't want to speak for him, but @jcrist is wrapping up a refactor that will reduce the "layers" in Ibis-ML. Hopefully some of this will resonate.
I can say that Ibis-ML was designed with intentional differences from scikit-learn (it's more tidymodels-inpired), but, again, @jcrist can definitely elaborate better on some of these points at this time, as the original author.
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Thanks for the context! I essentially opened issue to share the bug in the code snippet, so feel free to close the issue
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Related Issues (20)
- feat(steps): handle unknown category for all encoders HOT 2
- bug(steps): treat null values as proper categories
- feat: add serializer and deserializer for recipe HOT 3
- docs(tutorial): remove repeated backend connection
- docs(website): add support matrix HOT 3
- test(steps): add unit tests for `CategoricalEncode` step
- refactor(steps): rename `CategoricalEncode` to `OrdinalEncode`
- docs(website): create skeleton for new FAQ section
- bug(bigquery): invalid field name Cast(y, int64) in bigquery HOT 1
- bug(steps): handle col with all nulls in impute
- bug(steps): handle col with one unique value in Scale* step HOT 1
- bug(steps): remove set_categories in ExpandDate/Time steps HOT 5
- docs(examples): create demos on large data volumes
- Quickstart seems broken HOT 3
- ibis_ml has no attribute datetime HOT 1
- How to use `get_params()` HOT 9
- IbisML and GridSearchCV HOT 8
- AttributeError: 'list' object has no attribute 'fit_table' HOT 2
- refactor(utils): use column names that won't exist
- feat: add Select() step
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