Collaborating filtering
cf [-h] [-v] -i string [-n int] [-o string] [-q string] [-R int] [-r int] -V
This program performs collaborative filtering (CF) on the given dataset. Given a list of user, item and preferences (--input_file) the program will output a set of recommendations for each user.
Optionally, the set of query users can be specified with the --query_file option. In addition, the number of recommendations to generate can be specified with the --recommendations (-r) parameter, and the number of similar users (the size of the neighborhood) to be considered when generating recommendations can be specified with the --neighborhood (-n) option.
The input file should contain a 3-column matrix of ratings, where the first column is the user, the second column is the item, and the third column is that user's rating of that item. Both the users and items should be numeric indices, not names. The indices are assumed to start from 0.
--input_file (-i) [string] Input dataset to perform CF on.
--help (-h) Default help info.
--info [string] Get help on a specific module or option. Default value ''.
--neighborhood (-n) [int] Size of the neighborhood of similar users to consider for each query user. Default value 5.
--output_file (-o) [string] File to save output recommendations to. Default value 'recommendations.csv'.
--query_file (-q) [string] List of users for which recommendations are to be generated (if unspecified, then recommendations are generated for all users). Default value ''.
--rank (-R) [int] Rank of decomposed matrices. Default value 2. --recommendations (-r) [int] Number of recommendations to generate for each query user. Default value 5.
--verbose (-v) Display informational messages and the full list of parameters and timers at the end of execution.
--version (-V) Display the version of mlpack.
For further information, including relevant papers, citations, and theory, consult the documentation found at http://www.mlpack.org or included with your distribution of MLPACK.