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License: Apache License 2.0
Code for the article: O. Gouvert, T. Oberlin, C. Févotte "Recommendation from Raw Data with Adaptive Compound Poisson Factorization" Implemented in Python 2.7. The repository contains: - model: the algorithms for the models described in the article, namely discrete compound Poisson factorization (dcPF), for different choices of element distributions: * logarithmic (dcpf_Log) * zero-truncated Poisson (dcpf_ZTP) * shifted geometric (dcpf_Geo) * shifted negative binomial (dcpf_sNB) - dataset: the subset of the Taste Profile dataset used in the article - script_dcpf_TPS.py is the script used for the experiments of the article - demo_dcpf.py is a small example of application of dcPF on synthetic data - In "function": some functions to calculate scores, borrowed from Dawen Liang
Any plan to release the code for Ordinal Non-negative Matrix Factorization for Recommendation
Thank you!
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