Comments (3)
commented on May 22, 2024
ekstrand on 2011-05-25 15:52:06 said:
Updating already-fixed tickets to 0.0.3 milestone.
Note: This comment has been automatically migrated from Bitbucket
Created by grouplens on 2013-02-01T21:55:39.291620+00:00, last updated: None
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commented on May 22, 2024
Michael Ekstrand [email protected] on 2011-03-29 19:52:49 said:
In [4f8687f2cc6b75016693e3130ff9b28cb24b4eaf]:
Rename similarity matrix build strategies (closes #42)
* Rename `SimilarityMatrixBuildStrategy` to `ItemItemModelBuildStrategy`
* Rename specific strategies to model build strategies
* Rename "Optimized" to "Sparse"
Note: This comment has been automatically migrated from Bitbucket
Created by grouplens on 2013-02-01T21:55:38.913077+00:00, last updated: None
from lenskit.
commented on May 22, 2024
Michael Ekstrand [email protected] on 2011-03-29 19:52:49 said:
In [3e5b69e55cf7234bee90fa0f51bfaa27f99ce318]:
Rename item-item model builder and refactor Guice config (refs #42)
* Rename `ItemItemRecommenderBuilder` to `ItemItemModelBuilder` to better reflect its role
* Introduce `ItemItemModelProvider` and use a `ProvidedBy` annotation on `ItemItemModel` to configure it by default
* Document how to configure `ItemRecommenderModule`.
Note: This comment has been automatically migrated from Bitbucket
Created by grouplens on 2013-02-01T21:55:38.546668+00:00, last updated: None
from lenskit.
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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