Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Joint Shapley values: a measure of joint feature importance   The Shapley value is one of the most widely used measures of feature
importance partly as it measures a feature's average effect on a model's
prediction. We introduce joint Shapley values, which directly extend Shapley's
axioms and intuitions: joint Shapley values measure a set of features' average
contribution to a model's prediction. We prove the uniqueness of joint Shapley
values, for any order of explanation. Results for games show that joint Shapley
values present different insights from existing interaction indices, which
assess the effect of a feature within a set of features. The joint Shapley
values provide intuitive results in ML attribution problems. With binary
features, we present a presence-adjusted global value that is more consistent
with local intuitions than the usual approach.

28
The categories of this paper are: alg-geom
3
The categories of this paper are: physics
33
The categories of this paper are: plasm-ph
20
The categories of this paper are: acc-phys
21
The categories of this paper are: adap-org
11
The categories of this paper are: hep-lat
35
The categories of this paper are: mtrl-th
37
The categories of this paper are: supr-con
32
The categories of this paper are: atom-ph
2
The categories of this paper are: math
29
The categories of this paper are: funct-an
8
The categories of this paper are: hep-ex
23
The categories of this paper are: solv-int
27
The categories of this paper are: comp-gas
0
The categories of this paper are: hep-ph
10
The categories of this paper are: q-bio