Comments (4)
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 2013-02-01T21:55:41.071375+00:00, last updated: None
from lenskit.
Michael Ekstrand [email protected] on 2011-04-20 20:47:12 said:
In [8c57491113afa0483656a7249626a41cb47342a8]:
Normalize cached user-user CF and update configuration (closes #43)
* Normalize CachingNeighborhoodFinder
* Abstract NF builder configuration into AbstractNeighborhoodFinderBuilder
* Make useruser.js use caching builder
Note: This comment has been automatically migrated from Bitbucket
Created by grouplens on 2013-02-01T21:55:40.737074+00:00, last updated: None
from lenskit.
Michael Ekstrand [email protected] on 2011-04-19 18:55:52 said:
In [64422ac59e592b0a62e1f20022b4f8bb68743496]:
Implement simple NF normalization (refs #43)
* Add normalization support to SimpleNeighborhoodFinder
* Change default normalizer in useruser.js to user mean
Note: This comment has been automatically migrated from Bitbucket
Created by grouplens on 2013-02-01T21:55:40.375117+00:00, last updated: None
from lenskit.
Michael Ekstrand [email protected] on 2011-04-19 18:38:30 said:
In [d851632d1ed33889dd2f280f9f4080a5658d37d1]:
Normalize the prediction phase of user-user CF (refs #43)
Note: This comment has been automatically migrated from Bitbucket
Created by grouplens on 2013-02-01T21:55:39.983674+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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