Collaborative Filtering with multi-process parallelism.
Project description
Usage Sample ''''''''''''
.. code:: python
from cf import CollFilter
if __name__ == '__main__':
data = read_data('file_path')
data = pre_process(data) # return [(user_id: Any, item_id: Any, float),]
cf = CollFilter(data)
ucf = cf.user_cf() # return {user_id: [(item_id, score),],}
icf = cf.item_cf() # return {user_id: [(item_id, score),],}
recommend = cf.recommend(user_id, recall_num=5) # return [(item_id, score),]
recommends = cf.recommends(user_ids, recall_num=5) # return {user_id: [(item_id, score),],}
cf.release()
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
coll-filter-1.2.5.tar.gz
(7.0 kB
view details)
File details
Details for the file coll-filter-1.2.5.tar.gz
.
File metadata
- Download URL: coll-filter-1.2.5.tar.gz
- Upload date:
- Size: 7.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.9.18
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 9970e88d4b76fe2dedc8a90a7b619cf65165bd263354562abf9529c076853bfb |
|
MD5 | 0f13359250ed4050688319a18e5c5a45 |
|
BLAKE2b-256 | fb0c02401e66db28b56402c2c1e0e7444c8e72de635f32aa7030afea8ee0741c |