LensKit recommender toolkit - OLD. Use Google Group: https://groups.google.com/forum/#!forum/lenskit-recsys
are there any common pitfalls that lead to 0 recommended items? @mdekstrand
What algorithm & configuration are you using?
private static LenskitConfiguration getAlgorithmConfig() {
LenskitConfiguration cfg = new LenskitConfiguration();
// lenskit.org/documentation/algorithms/user-user/
cfg.bind(ItemScorer.class).to(UserUserItemScorer.class);
cfg.bind(BaselineScorer.class, ItemScorer.class).to(UserMeanItemScorer.class);
cfg.bind(UserMeanBaseline.class, ItemScorer.class).to(ItemMeanRatingItemScorer.class);
cfg.within(UserVectorNormalizer.class).bind(VectorNormalizer.class).to(MeanCenteringVectorNormalizer.class);
cfg.set(NeighborhoodSize.class).to(30);
return cfg;
}
private static EventDAO getEventDAO(String dataPath) {
File file = new File(dataPath);
EventFormat fmt = DelimitedColumnEventFormat
.create(LikeBuilder.class)
.setFields("user", "item", "timestamp")
.setDelimiter(",");
return TextEventDAO.create(file, fmt, CompressionMode.AUTO);
}
// user passed in
Long uid = Long.valueOf(user.getId());
LenskitConfiguration cfg = getAlgorithmConfig();
EventDAO dao = getEventDAO("dataset.csv");
cfg.addComponent(dao);
LenskitRecommenderEngine engine = LenskitRecommenderEngine.build(cfg);
ItemRecommender recommender = engine.createRecommender(cfg).getItemRecommender();
ResultList items = recommender.recommendWithDetails(uid, 10, null, null); // 0 items
the user I’m testing with has history
@mdekstrand
Most likely scenario is that it can't find any items the user has not rated that for which neighborhoods can be computed.
@smartinio
For real applications i recommend Logback.
Its configuration file will letyou set a logging level, output log files, etc.
Hello Lenskit Team,
We are working on a recommender project and would like to use the Lenskit SVD algorithm by Simon Funk.
We configured our model as shown on http://lenskit.org/documentation/algorithms/svd/
Our question: It is enough to just hand over the sparse User-Item-Rating Matrix, right?
How can we do that (A code snippet of such a call would be nice)
Thanks a lot!
Best,
CarKla
(we're working on fixing this, but that code is still in progress)
Hi @mdekstrand, I'm looking to use LensKit in the context of an actual application performing recommending, and I had a few questions
I've set up the configuration very similarly to the tutorial for now, like so:
LenskitConfiguration config = new LenskitConfiguration();
config.bind(ItemScorer.class).to(ItemItemScorer.class);
config.bind(BaselineScorer.class, ItemScorer.class).to(UserMeanItemScorer.class);
config.bind(UserMeanBaseline.class, ItemScorer.class).to(ItemMeanRatingItemScorer.class);
config.bind(UserVectorNormalizer.class).to(BaselineSubtractingUserVectorNormalizer.class);
config.bind(EventDAO.class).to(this.createDAO());
PreferenceDomainBuilder pdbuilder = new PreferenceDomainBuilder(-10, 10).setPrecision(0.01);
PreferenceDomain pd = pdbuilder.build();
config.bind(PreferenceDomain.class).to(pd);
LenskitRecommender rec = LenskitRecommender.build(config);
RatingPredictor pred = rec.getRatingPredictor();
double predicted = pred.predict(userId, jokeId);Will the predicted value be de-normalized? And if I ask for an existing value, should it match exactly or only closely? Lastly, is there a way to add a single rating to a LenskitRecommender without rebuilding it?
(2) closely - it will generate a prediction, it will not return the existing rating.
(3) not currently
@ezfe hope that helps
Hi, I was just wondering if you happen to know why lenskit is not available at Kaggle Kernel to be added as a custom package (not with pip nor from github which I don`t know if is any different). The output from their interface is only "Error: The command '/bin/sh -c pip install git+https://github.com/lenskit/lkpy' returned a non-zero code: 1" Thanks!
The pip install does work elsewhere, or at least it did last I tested it.
Do Kaggle kernels support Conda packages?
I don´t think they do support conda, their only option in their UI is pip (from github)
The PyPI version may have a dependency that doesn't work on Kaggle.
I tried both, but failed every time. Tried it again and still same output:
Thanks for your time @mdekstrand either way. I tried reaching Kaggle's Q&A (https://www.kaggle.com/questions-and-answers/71160#418923) with no results yet. If it`s not something that you would be able to easily fix, I can just wait for any idea on Kaggle's side and then just leave it be, I guess.
Kaggle's Python image already includes Numba and llvmlite, installed via Conda, but LensKit requires a newer version.
Pip canot upgrade the Conda versions to those required by LensKit, so the install fails
I expect it will probably work the next time Kaggle rebuilds their Python base image.
it does look like older Numba is ok (all tests pass), so I have downgraded that minimum version
@NickKartha the Getting Started guide walks through setting up a couple of algorithms: http://lkpy.lenskit.org/en/latest/GettingStarted.html
This channel is attached to the Java LensKit repository. It is now deprecated. I don't know if we'll use Gitter or not for the Python code, but in the mean time, use the Google Group: https://groups.google.com/forum/#!forum/lenskit-recsys