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What does the pair of vertical lines in empirical entropy formula mean?
Is it ok to interprete PCA plot this way?What is the Q function and what is the V function in reinforcement learning?Image Captioning example in keras Approach?What is this formula, related to simple linear regression, called?PCA algorithm problems - PythonWhat does “likelihood” mean in the image?Clamping Q function to it's theoretical maximum, yes or no?How does binary cross entropy work?learning curve SklearnQ learning transition matrix trouble
$begingroup$
I am learning from this post.
$alpha$ is the ratio of the first subset,
$$alpha=fracD_1rightleft$$
according to the context and code of the post, $left|Dright|$ means the number of samples?
- What are the pair of vertical lines called?
Is it the L1 norm symbol? It does not seem to be the absolute value symbol.
machine-learning notation
asked 15 hours ago
JayJay
1424
$endgroup$
add a comment |
$begingroup$
I am learning from this post.
$alpha$ is the ratio of the first subset,
$$alpha=fracD_1rightleft$$
according to the context and code of the post, $left|Dright|$ means the number of samples?
- What are the pair of vertical lines called?
Is it the L1 norm symbol? It does not seem to be the absolute value symbol.
machine-learning notation
asked 15 hours ago
JayJay
1424
$endgroup$
add a comment |
$begingroup$
I am learning from this post.
$alpha$ is the ratio of the first subset,
$$alpha=fracD_1rightleft$$
according to the context and code of the post, $left|Dright|$ means the number of samples?
- What are the pair of vertical lines called?
Is it the L1 norm symbol? It does not seem to be the absolute value symbol.
machine-learning notation
asked 15 hours ago
JayJay
1424
$endgroup$
I am learning from this post.
$alpha$ is the ratio of the first subset,
$$alpha=fracD_1rightleft$$
according to the context and code of the post, $left|Dright|$ means the number of samples?
- What are the pair of vertical lines called?
Is it the L1 norm symbol? It does not seem to be the absolute value symbol.
machine-learning notation
machine-learning notation
asked 15 hours ago
JayJay
1424
asked 15 hours ago
JayJay
1424
edited 1 hour ago
Jay
asked 15 hours ago
JayJay
1424
asked 15 hours ago
JayJay
1424
asked 15 hours ago
JayJay
1424
1424
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
$begingroup$
$D$ is a set which is further divided into sets $D_1$ and $D_2$. In this context the vertical lines represent the cardinality of the set i.e. the number of elements in the set. Hence, $alpha$ represents the ratio of number of samples of $D_1$ to $D$.
answered 14 hours ago
bkshibkshi
900415
$endgroup$
add a comment |
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1 Answer
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oldest
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1 Answer
1
active
oldest
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active
oldest
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active
oldest
votes
$begingroup$
$D$ is a set which is further divided into sets $D_1$ and $D_2$. In this context the vertical lines represent the cardinality of the set i.e. the number of elements in the set. Hence, $alpha$ represents the ratio of number of samples of $D_1$ to $D$.
answered 14 hours ago
bkshibkshi
900415
$endgroup$
add a comment |
$begingroup$
$D$ is a set which is further divided into sets $D_1$ and $D_2$. In this context the vertical lines represent the cardinality of the set i.e. the number of elements in the set. Hence, $alpha$ represents the ratio of number of samples of $D_1$ to $D$.
answered 14 hours ago
bkshibkshi
900415
$endgroup$
add a comment |
$begingroup$
$D$ is a set which is further divided into sets $D_1$ and $D_2$. In this context the vertical lines represent the cardinality of the set i.e. the number of elements in the set. Hence, $alpha$ represents the ratio of number of samples of $D_1$ to $D$.
answered 14 hours ago
bkshibkshi
900415
$endgroup$
$D$ is a set which is further divided into sets $D_1$ and $D_2$. In this context the vertical lines represent the cardinality of the set i.e. the number of elements in the set. Hence, $alpha$ represents the ratio of number of samples of $D_1$ to $D$.
answered 14 hours ago
bkshibkshi
900415
answered 14 hours ago
bkshibkshi
900415
answered 14 hours ago
bkshibkshi
900415
answered 14 hours ago
bkshibkshi
900415
900415
add a comment |
add a comment |
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