Meaning of this notion in 0-1 loss?












1












$begingroup$


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



weighted 0-1 loss










share|improve this question









New contributor




J. Doe is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.







$endgroup$












  • $begingroup$
    Your assumption is right.
    $endgroup$
    – Alireza Zolanvari
    19 hours ago
















1












$begingroup$


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



weighted 0-1 loss










share|improve this question









New contributor




J. Doe is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.







$endgroup$












  • $begingroup$
    Your assumption is right.
    $endgroup$
    – Alireza Zolanvari
    19 hours ago














1












1








1





$begingroup$


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



weighted 0-1 loss










share|improve this question









New contributor




J. Doe is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.







$endgroup$




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



weighted 0-1 loss







machine-learning loss-function math






share|improve this question









New contributor




J. Doe is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.











share|improve this question









New contributor




J. Doe is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.









share|improve this question




share|improve this question








edited 17 hours ago









Siong Thye Goh

1,367519




1,367519






New contributor




J. Doe is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.









asked 19 hours ago









J. DoeJ. Doe

82




82




New contributor




J. Doe is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.





New contributor





J. Doe is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.






J. Doe is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.












  • $begingroup$
    Your assumption is right.
    $endgroup$
    – Alireza Zolanvari
    19 hours ago


















  • $begingroup$
    Your assumption is right.
    $endgroup$
    – Alireza Zolanvari
    19 hours ago
















$begingroup$
Your assumption is right.
$endgroup$
– Alireza Zolanvari
19 hours ago




$begingroup$
Your assumption is right.
$endgroup$
– Alireza Zolanvari
19 hours ago










1 Answer
1






active

oldest

votes


















2












$begingroup$

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



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






share|improve this answer









$endgroup$













  • $begingroup$
    Also since both $I_{{Y=1}}$ and $I_{{y=1}}$ are present in the question. It is worth noting that $Z=I_{{Y=1}}$ is a random variable like $Z=2Y$ with a distribution, unlike $f(y)=I_{{y=1}}$ which is a function with no distribution.
    $endgroup$
    – Esmailian
    16 hours ago











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1 Answer
1






active

oldest

votes








1 Answer
1






active

oldest

votes









active

oldest

votes






active

oldest

votes









2












$begingroup$

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



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






share|improve this answer









$endgroup$













  • $begingroup$
    Also since both $I_{{Y=1}}$ and $I_{{y=1}}$ are present in the question. It is worth noting that $Z=I_{{Y=1}}$ is a random variable like $Z=2Y$ with a distribution, unlike $f(y)=I_{{y=1}}$ which is a function with no distribution.
    $endgroup$
    – Esmailian
    16 hours ago
















2












$begingroup$

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



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






share|improve this answer









$endgroup$













  • $begingroup$
    Also since both $I_{{Y=1}}$ and $I_{{y=1}}$ are present in the question. It is worth noting that $Z=I_{{Y=1}}$ is a random variable like $Z=2Y$ with a distribution, unlike $f(y)=I_{{y=1}}$ which is a function with no distribution.
    $endgroup$
    – Esmailian
    16 hours ago














2












2








2





$begingroup$

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



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






share|improve this answer









$endgroup$



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



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







share|improve this answer












share|improve this answer



share|improve this answer










answered 17 hours ago









Siong Thye GohSiong Thye Goh

1,367519




1,367519












  • $begingroup$
    Also since both $I_{{Y=1}}$ and $I_{{y=1}}$ are present in the question. It is worth noting that $Z=I_{{Y=1}}$ is a random variable like $Z=2Y$ with a distribution, unlike $f(y)=I_{{y=1}}$ which is a function with no distribution.
    $endgroup$
    – Esmailian
    16 hours ago


















  • $begingroup$
    Also since both $I_{{Y=1}}$ and $I_{{y=1}}$ are present in the question. It is worth noting that $Z=I_{{Y=1}}$ is a random variable like $Z=2Y$ with a distribution, unlike $f(y)=I_{{y=1}}$ which is a function with no distribution.
    $endgroup$
    – Esmailian
    16 hours ago
















$begingroup$
Also since both $I_{{Y=1}}$ and $I_{{y=1}}$ are present in the question. It is worth noting that $Z=I_{{Y=1}}$ is a random variable like $Z=2Y$ with a distribution, unlike $f(y)=I_{{y=1}}$ which is a function with no distribution.
$endgroup$
– Esmailian
16 hours ago




$begingroup$
Also since both $I_{{Y=1}}$ and $I_{{y=1}}$ are present in the question. It is worth noting that $Z=I_{{Y=1}}$ is a random variable like $Z=2Y$ with a distribution, unlike $f(y)=I_{{y=1}}$ which is a function with no distribution.
$endgroup$
– Esmailian
16 hours ago










J. Doe is a new contributor. Be nice, and check out our Code of Conduct.










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