Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Modeling morphology with Linear Discriminative Learning: considerations
  and design choices   This study addresses a series of methodological questions that arise when
modeling inflectional morphology with Linear Discriminative Learning. Taking
the semi-productive German noun system as example, we illustrate how decisions
made about the representation of form and meaning influence model performance.
We clarify that for modeling frequency effects in learning, it is essential to
make use of incremental learning rather than the endstate of learning. We also
discuss how the model can be set up to approximate the learning of inflected
words in context. In addition, we illustrate how in this approach the wug task
can be modeled in considerable detail. In general, the model provides an
excellent memory for known words, but appropriately shows more limited
performance for unseen data, in line with the semi-productivity of German noun
inflection and generalization performance of native German speakers.

37
The categories of this paper are: supr-con
0
The categories of this paper are: hep-ph
28
The categories of this paper are: alg-geom
25
The categories of this paper are: patt-sol
24
The categories of this paper are: dg-ga
22
The categories of this paper are: chao-dyn
20
The categories of this paper are: acc-phys
3
The categories of this paper are: physics
18
The categories of this paper are: econ
12
The categories of this paper are: nucl-th
13
The categories of this paper are: quant-ph
5
The categories of this paper are: gr-qc
16
The categories of this paper are: stat
8
The categories of this paper are: hep-ex
10
The categories of this paper are: q-bio
30
The categories of this paper are: q-alg