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README.md

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[![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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Implementation of data fusion methods in Julia, specifically **Macau**, **BPMF**.
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Implementation of data fusion methods in Julia, specifically **Macau**, **BPMF** (Bayesian Probabilistic Matrix Factorization). Supported features:
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* Factorization of matrices (without or with side information)
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* Factorization of tensors (without or with side information)
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* Co-factorization of multiple matrices and tensors (any side information is
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possible)
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* Side information inside relation
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* Parallelization (multi-core and multi-node)
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BayesianDataFusion uses Gibbs sampling to learn the latent vectors and link
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matrices. In addition to predictions Gibbs sampling also provides estimates
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of **standard deviation** and possible other metrics (that can be computed from
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samples).
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## Installation
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```julia

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