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This is just another tutorial on logistic regression.
The purpose of logistic regression is to identify equation of a cuvre which distinguishes two classes which exist in two or higher dimensions, but in this present tutorial we will keep it simple and our data would just be two dimentional.
Consider the following data
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$$ {\bf{x}}_i $$ -
$$ \left( {\mathbf{x}}_i, {\tilde{y}}_i \right) $$
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$$ {\mathbf{x}}_i $$
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$$ { {\mathbf{x}}_i} $$
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$$ {\mathbb{R}^m} $$
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\( y = mx+c \)
\( y = mx+c \)
\[ y = mx+c \]
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When something is important enough, you do it even if the odds are not in your favor.
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- This is an ordered list following a header.
head1 | head two | three |
---|---|---|
ok | good swedish fish | nice |
out of stock | good and plenty | nice |
ok | good oreos |
hmm |
ok | good zoute drop |
yumm |
- Item foo
- Item bar
- Item baz
- Item zip
- Item one
- Item two
- Item three
- Item four
- level 1 item
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- level 1 item
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- Name
- Godzilla
- Born
- 1952
- Birthplace
- Japan
- Color
- Green
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The final element.