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Description: A user-preference-sensitive collaborative filtering algorithm for recommender system, which is based on items' ratings.
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Optimization Method: batch gradient descent
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Parameter Initialization Method: normal distribution
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Ensemble Method: voting
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Output: a dictionary of recommendations
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Other Features: flexible choices of the dimension of item's feature, training epochs, etc.
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Released on PyPI. A user-preference-sensitive collaborative filtering algorithm for recommender system, which is based on items' ratings.
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Kaversoniano/Python-package-RatingCF
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Released on PyPI. A user-preference-sensitive collaborative filtering algorithm for recommender system, which is based on items' ratings.
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