Meaning of this notion in 0-1 loss? I am reading a paper and encountered this notion:

$$1_{\{Y=1\}}$$

To me it seems to be the expression as below, but I am not entirely sure and I don't think the author explictly explained it: 

if Y==1:
  return 1
else:
  return 0


Can someone help me to clarify this notion? Much thanks for your time (:



It appears in:

https://papers.nips.cc/paper/5073-learning-with-noisy-labels.pdf
Your understanding is correct. 

This is known as the indicator function.

The indicator function of a subset $A$ of a set $X$ is a function

$$1_A(x)= \begin{cases}1, &amp; x \in A \\ 0, &amp; x \notin A \end{cases}$$