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home.rst.txt
Welcome to LightFM's documentation! ========== LightFM is a Python implementation of a number of popular recommendation algorithms for both implicit and explicit feedback. It also makes it possible...making.lyst.com/lightfm/docs/_sources/home.rst.txtRegistered: Fri May 03 08:06:38 UTC 2024 - Last Modified: Wed Mar 09 16:56:08 UTC 2022 - 6.8K bytes - Viewed (0) -
movielens_implicit.rst.txt
An implicit feedback recommender for the Movielens dataset ========== Implicit feedback ---------- For some time, the recommender system literature focused on explicit feedback: the Netflix prize f...making.lyst.com/lightfm/docs/_sources/examples/movielens_implicit.rst.txtRegistered: Fri May 03 08:06:42 UTC 2024 - Last Modified: Wed Mar 09 16:56:08 UTC 2022 - 5.7K bytes - Viewed (2) -
warp_loss.rst.txt
Learning-to-rank using the WARP loss ========== LightFM is probably the only recommender package implementing the WARP (Weighted Approximate-Rank Pairwise) loss for implicit feedback learning-to-ra...making.lyst.com/lightfm/docs/_sources/examples/warp_loss.rst.txtRegistered: Fri May 03 08:06:45 UTC 2024 - Last Modified: Wed Mar 09 16:56:08 UTC 2022 - 6.9K bytes - Viewed (0) -
lightfm.rst.txt
LightFM ========== .. autoclass:: lightfm.LightFM :members: :undoc-members:making.lyst.com/lightfm/docs/_sources/lightfm.rst.txtRegistered: Fri May 03 08:06:27 UTC 2024 - Last Modified: Wed Mar 09 16:56:08 UTC 2022 - 88 bytes - Viewed (1) -
dataset.rst.txt
Building datasets ========== In this example, we'll use LightFM's built-in ``Dataset`` class to build an interaction dataset from raw data. The goal is to demonstrate how to go from raw data (lists...making.lyst.com/lightfm/docs/_sources/examples/dataset.rst.txtRegistered: Fri May 03 08:06:49 UTC 2024 - Last Modified: Wed Mar 09 16:56:08 UTC 2022 - 6K bytes - Viewed (0)