This function takes a model (e.g., projector or bi_projector) and a new dataset,
and computes the rank-d approximation of the new data in the same subspace that
was defined by the model. In other words, we project the new data into
the fitted subspace and then map it back to the original dimensionality.
reconstruct_new(x, new_data, ...)A numeric matrix (same number of rows as new_data, and typically
the same number of columns if you're reconstructing fully) representing the
rank-d approximation in the model's subspace.
The fitted model object (e.g., bi_projector) that defines
a subspace or factorization.
A numeric matrix (or data frame) of shape
(n x p_full) or possibly fewer columns if you allow partial reconstruction.
Additional arguments passed to the specific reconstruct_new method
for the class of x.
Similar to reconstruct but operates on an external new_data
rather than the original fitted data. Often used to see how well the model's
subspace explains unseen data.
reconstruct for reconstructing the original data in the model.
Other reconstruct:
reconstruct()