Bayesian Tensor Factorization
A function for generating a default set of parameters for Bayesian Ten...
Preprocessing: fiber Centering
Preprocessing: Slab Scaling
Plot Tensor Components
Predict Missing Values using the Bayesian tensor factorization model
Reconstruct the data based on posterior samples
Bayesian Factorization of a Tensor
Postprocessing: Undo fiber Centering
Postprocessing: Undo Slab Scaling
Bayesian Tensor Factorization for decomposition of tensor data sets using the trilinear CANDECOMP/PARAFAC (CP) factorization, with automatic component selection. The complete data analysis pipeline is provided, including functions and recommendations for data normalization and model definition, as well as missing value prediction and model visualization. The method performs factorization for three-way tensor datasets and the inference is implemented with Gibbs sampling.