Release notes for LensKit 1.1

The Git changelog and the list of closed tickets and pull requests provide more information on what has happened, including bugs that have been fixed.

This release requires some recommender configuration changes, as well as changes to any custom components depending on LensKit parameter annotations; see Upgrading to LensKit 1.1 for details on how to do this.

There are quite a few changes in LensKit 1.1; this list is not exhaustive, but tries to capture highlights and things that will affect current users.

• Made Recommender extend Closeable (#issue(315)).

• Added side channel support to sparse vectors (#issue(185)).

• Added support for at context matchers (via Grapht), to make it easier to configure complex configurations. See the manual for more details.

• Made SparseVector constructors package-private. Sparse vectors shouldn’t be subclassed by any additional classes.

• Config change: introduced predict methods to RatingPredictor, deprecating the fact that it extends ItemScorer (#issue(164)). As a result, all algorithm item scorers now implement ItemScorer, not RatingPredictor, and new rating predictors fill in the old jobs. The upgrading guide, #164, and #311 contain more details.

• Incompatible change: moved abstract and simple/score-based implementations of basic recommender components to the new package o.g.l.basic. This should only be incompatible for people implementing new LensKit components.

• Config change: Removed dedicated params packages, moving parameters to saner locations (#issue(294)). See the upgrading guide for details.

• Many little cleanups and bug-fixes.

• Lots more automatic testing support.

Algorithms

• Item-item scorers now report the number of neighbors used for each score as a side channel.

• Deprecated algorithm-specific item recommenders in favor of using ScoreBasedItemRecommender directly.

• Added LeastSquaresPredictor, a baseline predictor that uses gradient descent to train per-item and per-user baseline values (à la Koren et al.).

k-NN Recommenders

• Default change: changed default ModelSize to 0 (all neighbors retained); by default, item-item models now retain all neighbors with nonnegative similarities.

• Default change: Changed the default value for ModelSize to 20 (was 30).

• Refactored the item-item recommender to get rid of ItemItemModelBackedScorer, simplifying the class hierarchy and configuration.

• Replaced LongScoredList with a list of ScoredId objects in Item-Item model construction to support side channels (#issue(219)).

Funk-SVD

• Incompatible change: moved iterative support code to o.g.l.iterative and changed parameters. The StoppingCondition interface and implementations now live in this package; common iterative method parameters are now defined by annotations in o.g.l.iterative.

  • IterationCount is moved to the new package.

  • MinimumIterations is moved to the new package.

  • Threshold stopping conditions now use StoppingThreshold in this package instead of ThresholdValue. If you configure the threshold value, update your configuration accordingly.

  • The FunkSVD LearningRate and RegularizationTerm have been moved to the new iterative parameters package.

  • Config change: Changed the default value for MinimumIterations to 10.

• Added several new configuration points to the Funk-SVD model builder

Evaluator

• TrainTestEvalCommand now returns Table, not TableImpl.

• Eval configuration changes

  • Force and thread count are now runtime parameters, not script parameters. Specify them with --force and --thread-count command line options, or the corresponding eval mojo options.

  • Commands receive the eval configuration via the setConfig method.

• Added a trainModel command that trains a model and applies arbitrary functions to it.

• Table changes:

  • Tables now live in o.g.l.util.table.

  • TableImpl is now package-private and immutable; use TableBuilder to build a table.

  • InMemoryWriter is replaced with TableBuilder, which implements TableWriter.

  • Table layouts now live directly in the table package.

  • Table writers now live in o.g.l.util.table.writer.

• Many improvements to the dumpGraph command (#issue(264)).

• AbstractCommand now allows for the name to be null, although null names can never be exposed to callers.

• Added run-r goal to the Maven plugin to run R.

• Added the lenskit-publish phase to the LensKit evaluation lifecycle as a place to hook in and generate reports that use the output of lenskit-analyze.

• Added the subsample command to subsample a data set.

Train-Test Evaluator

• Train-test evaluator always runs, even if output is up-to-date with respect to input; use the lenskit.eval.skip Maven property to disable the evaluator when running it via Maven and you only want to run post-eval analysis phases.

• Train-test evaluator now has predictionChannel directive to write side channel values out to the prediction output file.

• Added retain directive to the trainTest command to retain a fixed number of items per user.

• Deprecated the holdout directive on trainTest that takes a fraction in favor of the clearer holdoutFraction directive.

• Add the ability for metric to take an arbitrary function to compute metrics over an algorithm, and multiMetric to compute multiple metrics per algorithm.

• Added the externalAlgorithm directive to allow algorithms implemented in external processes to be evaluated.

Archetypes

• Added lenskit-archetype-fancy-analysis archetype to provide a template for more sophisticated LensKit experimental setups.

• Improved the simple archetype to use the new R mojo.