Surprise v0.0.4 Release Notes
Release Date: 2016-11-15 // over 7 years ago-
Date: 15/11/16
โจ Enhancements
- โ Added notebooks for comparing and evaluating algorithm performances
- ๐ Better use of setup.py
- โ Added a min_support parameter to the similarity measures.
- โ Added a min_k parameter to the KNN algorithms.
- The similarity matrix and baselines are now returned.
- โ You can now train on a whole training set without test set.
- The estimate method can return a tuple with prediction details.
- โ Added SVD and SVD++ algorithms.
- โ Removed all the x/y vs user/item stuff. That was useless for most algorithms.
API Changes
- โ Removed the @property decorator for many iterators.
- It's now up to the algorithms to decide if they can or cannot make a prediction.