Hi Christoph,
the thing with the current implementation of the SparseVector is that you
can only modify entries which are “non-zero”. All other entries are not
represented in the underlying data structures. This means that you have to
create a new SparseVector if you want to set a zero entry to no
Hi,
Felix and I are currently working on the implementation of the FeatureHasher
(Issue #1735), which in the end returns a SparseVector.
When using “SparseVector.fromCOO" I’m facing some odd behaviour I haven’t
expected.
Assume I create a SparseVector.fromCOO(numFeatures, Map((0, 1.0), (1, 1.0
