Closed iamjli closed 6 years ago
Hey @iamjli, This would probably be best posted in the main tensorly repo. The issue comes from the fact that you are only passing one rank (int) instead of a list (one rank for each of the three modes, i.e. the dimension of the core). Also you probably want to assign the result to a core and a list of factors.
In code:
core, factors = non_negative_tucker(X, ranks=[2, 2, 2])
The error should be more informative though and we could use the rank provided for all modes, will change this!
Hello! I am receiving an error when performing nonnegative Tucker decomposition. Regular Tucker decomposition works fine, and so does PARAFAC and nonnegative PARAFAC.