Comments (2)
Thx, this code now only consider the most popular metric in rank issue and all metrics are in daisy.utils.metrics
. For your issue, I think F1-score could be calculated by precision and recall, and AUC is also available in other way.
This version of daisy is still an experimental code, not a package. Therefore, I will update and release it to a more complete version after our paper got published.
I will update these metrics after Feb. 2020๏ผand you can also fork this repo and add these metrics. I'd like merge your request.
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This is a good project!
But can u add some ctr prediction metrics such as 'AUC' or 'F1'๏ผ
I think add it is easy, and it will be more helpful.
I've already update metrics.py
, add new metrics like AUC, F1-score. Enjoy it!
daisyRec/daisy/utils/metrics.py
Line 121 in f8b76ca
daisyRec/daisy/utils/metrics.py
Line 140 in f8b76ca
from daisyrec.
Related Issues (10)
- ModuleNotFoundError: No module named '...' HOT 2
- JSONDecode Error HOT 1
- Is DaisyRec going to have session-based recommenders? HOT 2
- Bug in CDAE model about out_activation HOT 1
- Paper availability? HOT 2
- the parameter test_method='ufo' in daisy.utils.splitter.split_test() HOT 1
- The problem with the <UNK> in the oitems variable returned by the skip-gram function in the Item2Vec model HOT 3
- Yelp dataset statistics HOT 4
- Why can MRR be bigger than 1? HOT 2
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