Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: How to "DODGE" Complex Software Analytics?   Machine learning techniques applied to software engineering tasks can be
improved by hyperparameter optimization, i.e., automatic tools that find good
settings for a learner's control parameters.
  We show that such hyperparameter optimization can be unnecessarily slow,
particularly when the optimizers waste time exploring "redundant tunings"',
i.e., pairs of tunings which lead to indistinguishable results. By ignoring
redundant tunings, DODGE, a tuning tool, runs orders of magnitude faster, while
also generating learners with more accurate predictions than seen in prior
state-of-the-art approaches.

19
The categories of this paper are: eess
37
The categories of this paper are: supr-con
18
The categories of this paper are: econ
17
The categories of this paper are: q-fin
4
The categories of this paper are: cond-mat
14
The categories of this paper are: math-ph
30
The categories of this paper are: q-alg
29
The categories of this paper are: funct-an
5
The categories of this paper are: gr-qc
22
The categories of this paper are: chao-dyn
28
The categories of this paper are: alg-geom
6
The categories of this paper are: astro-ph
31
The categories of this paper are: ao-sci
8
The categories of this paper are: hep-ex
7
The categories of this paper are: hep-th
12
The categories of this paper are: nucl-th