Comments (3)
Commas are missing here:
all_scores = {
'SVD (best)': svd.evaluate()
'LightFM (best)': evaluate_lightfm(lfm)
f'HybridSVD (rank {hsvd.rank})': hsvd.evaluate()
}
Corrected
all_scores = {
'SVD (best)': svd.evaluate(),
'LightFM (best)': evaluate_lightfm(lfm),
f'HybridSVD (rank {hsvd.rank})': hsvd.evaluate()
}
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Replace :
trials_df = (study.trials_dataframe().loc[:, ['value', 'params', 'user_attrs']].rename(columns={'': target_metric}))
To:
trials_df = study.trials_dataframe().loc[:, ['value', 'params_rank', 'user_attrs_metrics','user_attrs_epochs']].rename(columns={'': target_metric})
from polara.
Hi! Thanks for reporting!
I'll have a look. There's a long-time-delayed update in my internal develop branch, I'll include the necessary modifications in the forthcoming release.
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Related Issues (14)
- Python 3 compatibility HOT 2
- LightFM feature normalization descreases precision HOT 2
- ModuleNotFoundError: No module named 'polara.recommender.hybrid' HOT 1
- Get recommendation from PureSVD model given user's preference HOT 8
- Scaled svd and hybrid svd is giving non deterministic output HOT 5
- polara.preprocessing module not found HOT 5
- ModuleNotFoundError: No module named 'polara' HOT 1
- NotImplementedError: Data has duplicate values HOT 2
- Precision@K HOT 1
- Conda and Pip package
- ModuleNotFoundError: No module named 'polara.recommender' HOT 5
- TypeError: __init__() got an unexpected keyword argument 'item_features' HOT 3
- TypeError: 'int' object is not iterable HOT 5
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