Comments (7)
TomAugspurger
commented on August 23, 2024
Cool, I've wanted to try it out on a real project for years.
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dsevero
commented on August 23, 2024
Great. I'll use it in whatever I try to do next (after the Imputer, which I don't think makes much sense).
Maybe we can start making some estimators?
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TomAugspurger
commented on August 23, 2024
Maybe we can start making some estimators?
By all means. Which ones are you interested in working on?
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dsevero
commented on August 23, 2024
I think it would be strategic to implement ALS. Spark has gained some spectacular popularity in recommendation systems due to it. There's an implementation of a somewhat similar method in sklearn, but I think it would be wise to go rogue on this one.
I've implemented it before by hand using the multiprocessing lib in python in the past. Should be quite easy to migrate it.
What do you think?
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TomAugspurger
commented on August 23, 2024
ALS seems like an ideal candidate.
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massich
commented on August 23, 2024
Hi I've also would like to play with hypothesis. How can I help? @daniel-severo can you point to where you had started to play with it?
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TomAugspurger
commented on August 23, 2024
I'm not familiar with using hypothesis, so I may be wrong, but I think it'd
be more straightforward to apply it
to pandas itself, rather than dask-ml. I opened
pandas-dev/pandas#17978 to
discuss using it in pandas.
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Hi I've also would like to play with hypothesis. How can I help?
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Related Issues (20)
- HashingVectorizer behaves differently from FeatureHasher HOT 1
- sklearn handles text labels differently than ml_dask on OneHotEncoding
- Implementation for make_s_curve HOT 2
- Import dask_ml with python 3.10 failed due to conflict with dask.distributed HOT 4
- Python 3.11 support HOT 2
- LogisticRegression.score returns an empty dask array
- Incremental does not handle dask arrays of ndim>2 in estimator training HOT 2
- loading dask_ml gives error contextualversionconflict with sklearn HOT 4
- For a single record data frame train_test_split() sometimes assigns this single record to test set. HOT 2
- The `log_loss`-function crashes when using mixed types
- Area under the receiving operating characteristic curve (AUROC) calculation. HOT 2
- The latest version doesn't support perceptron model
- sklearn StandardScaler vs dask StandardScaler. HOT 1
- Nearest Neighbors
- `TypeError` when predicting non-array data with `dask-expr` HOT 6
- Undeclared runtime dependency on setuptools HOT 1
- Documentation on PCA expected max memory usage HOT 1
- Support GPU-backed data for metrics.
- Unexpected behavior in train_test_split with shuffle=False
- ColumnTransformer does not work with Dask dataframes HOT 1
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