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33[ ![ Build Status] ( https://travis-ci.org/jaak-s/BayesianDataFusion.jl.svg?branch=master )] ( https://travis-ci.org/jaak-s/BayesianDataFusion.jl )
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5- Implementation of data fusion methods in Julia, specifically ** Macau** , ** BPMF** .
5+ Implementation of data fusion methods in Julia, specifically ** Macau** , ** BPMF** (Bayesian Probabilistic Matrix Factorization). Supported features:
6+ * Factorization of matrices (without or with side information)
7+ * Factorization of tensors (without or with side information)
8+ * Co-factorization of multiple matrices and tensors (any side information is
9+ possible)
10+ * Side information inside relation
11+ * Parallelization (multi-core and multi-node)
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13+ BayesianDataFusion uses Gibbs sampling to learn the latent vectors and link
14+ matrices. In addition to predictions Gibbs sampling also provides estimates
15+ of ** standard deviation** and possible other metrics (that can be computed from
16+ samples).
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718## Installation
819``` julia
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