Comments (7)
ekstrand on 2011-06-15 21:32:12 said:
This is now done.
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Created by grouplens on 2013-02-01T21:55:46.363675+00:00, last updated: None
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Michael Ekstrand [email protected] on 2011-06-15 20:36:08 said:
In [3675339fde95fb93a13f870e8ac44328cb329c06]:
Clean up naming and documentation of recommenders (refs #84, #47)
* Rename predictor-based recommenders
* Collapse Simple and Abstract predictor-based recommenders into single concrete classes
* Drop BasketRecommender
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ekstrand on 2011-06-13 20:47:48 said:
Still clearing up some naming on this.
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Michael Ekstrand [email protected] on 2011-06-13 20:27:48 said:
In [8ed7a58f7af2da18ef2f02bc67e2876853b3ee5d]:
Revert rename to restore `DynamicRatingItemRecommender` and friends (refs #47).
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Michael Ekstrand [email protected] on 2011-06-13 20:27:48 said:
In [d86e4631218ef82893dd2b2ba3a524f3c5c1db68]:
Merge recommender refactorying & impl (refs #47)
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Created by grouplens on 2013-02-01T21:55:44.879356+00:00, last updated: None
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[email protected] on 2011-06-13 20:27:48 said:
In [e4476be7a9fc89d9caa680ad57187cf1f64b6b4a]:
Review rating prediction/recommendation interface (closes #47).
* Removed the getPredictableItems method from all rating predictors.
* Added a getPredictableItems method to all rating recommenders.
* Revised AbstractRatingRecommender to include generic implementations of the getPredictableItems and the
recommend(long, SparseVector, int, LongSet, LongSet) methods.
* Added getPredictableItems and revised recommend(long, SparseVector, int, LongSet, LongSet) methods in
ItemItemRatingRecommender and UserUserRatingRecommender.
* Added the static method isComplete to SparseVector to determine if any keys are mapped to Double.NaN
* Fixed UserUserRatingRecommender to properly deal with null candidate sets. (Closes #62)
* Wrote JUnit test cases for all recommend methods implemented by ItemIItemRatingRecommender and
UserUserRatingRecommender.
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Created by grouplens on 2013-02-01T21:55:44.495543+00:00, last updated: None
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ekstrand on 2011-04-08 17:10:03 said:
If we do this, then we need to have a further BaselinePredictor
interface that preserves the SparseVector
methods.
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Created by grouplens on 2013-02-01T21:55:44.125554+00:00, last updated: None
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Related Issues (20)
- Support query/runtime data in train-test evaluation
- Support emitting query data from crossfolder
- Support Bellogin's evaluation methods
- Bad import detection is broken HOT 1
- Add option for evaluation to continue after a failed job
- Add setting to restrict parallel evaluations
- Create general-purpose score/recommend/rank APIs
- which algorithm does use the item feature(e.g. some features in ML-100k's u.item files) in Lenskit HOT 3
- Support frequency-based recommendation
- Implement hit rate metric
- Rating summary is asking for Rating entities for implicit feedback data HOT 5
- Isolated train-test sets do not work correctly
- Implement new-style JDBC DAO HOT 2
- Write eval results to a database
- Adding Parameter to IntelliJ IDEA HOT 1
- Investigate switching to LA4J HOT 3
- Remove SparseVector
- Create general-purpose Lucene-based recommender HOT 1
- Support count attributes in popularity statistics
- ItemRecommender documentation is vague on some details. HOT 4
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