How to transform features order to make their distribution normal?
$begingroup$
After sns.pairplot(df) command, I got this picture:
The question is what transformation to use in order to make the distributions normal?
Thank you
machine-learning python linear-regression
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bumped to the homepage by Community♦ 31 mins ago
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add a comment |
$begingroup$
After sns.pairplot(df) command, I got this picture:
The question is what transformation to use in order to make the distributions normal?
Thank you
machine-learning python linear-regression
$endgroup$
bumped to the homepage by Community♦ 31 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
After sns.pairplot(df) command, I got this picture:
The question is what transformation to use in order to make the distributions normal?
Thank you
machine-learning python linear-regression
$endgroup$
After sns.pairplot(df) command, I got this picture:
The question is what transformation to use in order to make the distributions normal?
Thank you
machine-learning python linear-regression
machine-learning python linear-regression
asked Nov 21 '18 at 23:36
Sukhrat ArziyevSukhrat Arziyev
61
61
bumped to the homepage by Community♦ 31 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
bumped to the homepage by Community♦ 31 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
add a comment |
1 Answer
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$begingroup$
Just looking at a pairplot isn't enough to suggest changes, in my opinion. Moreover, what are you trying to test? What is your null hypothesis, what is the alternative hypothesis? What kind of data is it, how neat was your collection process? Are there any co-variables?
With the info provided, all I can suggest is to perform parametric and non-parametric tests. May try Box-Cox transformation!
$endgroup$
add a comment |
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1 Answer
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1 Answer
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$begingroup$
Just looking at a pairplot isn't enough to suggest changes, in my opinion. Moreover, what are you trying to test? What is your null hypothesis, what is the alternative hypothesis? What kind of data is it, how neat was your collection process? Are there any co-variables?
With the info provided, all I can suggest is to perform parametric and non-parametric tests. May try Box-Cox transformation!
$endgroup$
add a comment |
$begingroup$
Just looking at a pairplot isn't enough to suggest changes, in my opinion. Moreover, what are you trying to test? What is your null hypothesis, what is the alternative hypothesis? What kind of data is it, how neat was your collection process? Are there any co-variables?
With the info provided, all I can suggest is to perform parametric and non-parametric tests. May try Box-Cox transformation!
$endgroup$
add a comment |
$begingroup$
Just looking at a pairplot isn't enough to suggest changes, in my opinion. Moreover, what are you trying to test? What is your null hypothesis, what is the alternative hypothesis? What kind of data is it, how neat was your collection process? Are there any co-variables?
With the info provided, all I can suggest is to perform parametric and non-parametric tests. May try Box-Cox transformation!
$endgroup$
Just looking at a pairplot isn't enough to suggest changes, in my opinion. Moreover, what are you trying to test? What is your null hypothesis, what is the alternative hypothesis? What kind of data is it, how neat was your collection process? Are there any co-variables?
With the info provided, all I can suggest is to perform parametric and non-parametric tests. May try Box-Cox transformation!
answered Nov 22 '18 at 11:48
Random NerdRandom Nerd
708
708
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