lenskit-predict
Name
lenskit predict - predict user ratings of items.
Synopsis
lenskit [GLOBAL OPTIONS] predict [OPTIONS] USER ITEM…
Description
The predict command predicts a user’s ratings for some items. It loads
a recommender from a trained model file and/or LensKit configuration
scripts and uses the configured algorithm to produce rating predictions.
Options
- USER
- The user ID for whom to generate predictions.
- ITEM
- An item ID to predict for.
- –help
- Show usage help.
- -m FILE, –model-file FILE
- Load a trained recommender engine from FILE.
- -c SCRIPT, –config-file SCRIPT
- Configure the recommender using SCRIPT. This option can be
specified multiple times, and later configurations take precedence
over earlier ones. If
--model-fileis also specified, the scripts are used to modify the trained model. - –print-channel CHAN
- In addition to rating predictions, also print the value in side channel CHAN.
This command also takes the standard input data options and script environment options.
See Also
lenskit(1), lenskit-input-data(7), lenskit-script-environment(7)
Project Information
This command is a part of LensKit, an open source recommender systems toolkit developed by GroupLens Research. Copyright 2010-2014 Regents of the University of Minnesota and contributors.
Work on LensKit has been funded by the National Science Foundation under grants IIS 05-34939, 08-08692, 08-12148, and 10-17697.
This program is free software; you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License as published by the Free Software Foundation; either version 2.1 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.