Meaning of this notion in 0-1 loss?
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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
machine-learning loss-function math
New contributor
$endgroup$
add a comment |
$begingroup$
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
machine-learning loss-function math
New contributor
$endgroup$
$begingroup$
Your assumption is right.
$endgroup$
– Alireza Zolanvari
19 hours ago
add a comment |
$begingroup$
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
machine-learning loss-function math
New contributor
$endgroup$
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
machine-learning loss-function math
machine-learning loss-function math
New contributor
New contributor
edited 17 hours ago
Siong Thye Goh
1,367519
1,367519
New contributor
asked 19 hours ago
J. DoeJ. Doe
82
82
New contributor
New contributor
$begingroup$
Your assumption is right.
$endgroup$
– Alireza Zolanvari
19 hours ago
add a comment |
$begingroup$
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
add a comment |
1 Answer
1
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votes
$begingroup$
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
$$1_A(x)= begin{cases}1, & x in A \ 0, & x notin A end{cases}$$
$endgroup$
$begingroup$
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
add a comment |
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1 Answer
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$begingroup$
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
$$1_A(x)= begin{cases}1, & x in A \ 0, & x notin A end{cases}$$
$endgroup$
$begingroup$
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
add a comment |
$begingroup$
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
$$1_A(x)= begin{cases}1, & x in A \ 0, & x notin A end{cases}$$
$endgroup$
$begingroup$
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
add a comment |
$begingroup$
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
$$1_A(x)= begin{cases}1, & x in A \ 0, & x notin A end{cases}$$
$endgroup$
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
$$1_A(x)= begin{cases}1, & x in A \ 0, & x notin A end{cases}$$
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
add a comment |
$begingroup$
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
add a comment |
J. Doe is a new contributor. Be nice, and check out our Code of Conduct.
J. Doe is a new contributor. Be nice, and check out our Code of Conduct.
J. Doe is a new contributor. Be nice, and check out our Code of Conduct.
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$begingroup$
Your assumption is right.
$endgroup$
– Alireza Zolanvari
19 hours ago