Hi,
in the ML-Pipeline of Flink we have the "LabeledVector" class. It
consists of a vector and a label as a double value. Unfortunately, it is
not applicable for sequence learning where the label is also a vector.
For example, in NLP we have a vector of words and the label is a vector
of the corresponding labels.
The optimize function of the "Solver" class has a DateSet[LabeledVector]
as input and, therefore, it is not applicable for sequence learning. I
think the LabeledVector should be adapted that the label is a vector
instead of a single Double value. What do you think?
Best Regards,
--
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Hilmi Yildirim, M.Sc.
Researcher
DFKI GmbH
Intelligente Analytik für Massendaten
DFKI Projektbüro Berlin
Alt-Moabit 91c
D-10559 Berlin
Phone: +49 30 23895 1814
E-Mail: hilmi.yildi...@dfki.de
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