Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Analytical Bounds between Entropy and Error Probability in Binary
  Classifications   The existing upper and lower bounds between entropy and error probability are
mostly derived from the inequality of the entropy relations, which could
introduce approximations into the analysis. We derive analytical bounds based
on the closed-form solutions of conditional entropy without involving any
approximation. Two basic types of classification errors are investigated in the
context of binary classification problems, namely, Bayesian and non-Bayesian
errors. We theoretically confirm that Fano's lower bound is an exact lower
bound for any types of classifier in a relation diagram of "error probability
vs. conditional entropy". The analytical upper bounds are achieved with respect
to the minimum prior probability, which are tighter than Kovalevskij's upper
bound.

15
The categories of this paper are: nucl-ex
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The categories of this paper are: eess
8
The categories of this paper are: hep-ex
27
The categories of this paper are: comp-gas
10
The categories of this paper are: q-bio
30
The categories of this paper are: q-alg
28
The categories of this paper are: alg-geom
18
The categories of this paper are: econ
34
The categories of this paper are: chem-ph
23
The categories of this paper are: solv-int
11
The categories of this paper are: hep-lat
35
The categories of this paper are: mtrl-th
16
The categories of this paper are: stat
0
The categories of this paper are: hep-ph
13
The categories of this paper are: quant-ph
17
The categories of this paper are: q-fin