Machine learning algorithm that uses the Pearson or Spearman correlation?
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I've come across linear and multiple regression, SVM, random forests. Does any know of a machine learning algorithm that uses the Pearson correlation or Spearman correlation?
Best,
Dave
machine-learning correlation
asked Jan 16 at 22:58
Dave NguyenDave Nguyen
1
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bumped to the homepage by Community♦ 13 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 |
$begingroup$
I've come across linear and multiple regression, SVM, random forests. Does any know of a machine learning algorithm that uses the Pearson correlation or Spearman correlation?
Best,
Dave
machine-learning correlation
asked Jan 16 at 22:58
Dave NguyenDave Nguyen
1
$endgroup$
bumped to the homepage by Community♦ 13 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 |
$begingroup$
I've come across linear and multiple regression, SVM, random forests. Does any know of a machine learning algorithm that uses the Pearson correlation or Spearman correlation?
Best,
Dave
machine-learning correlation
asked Jan 16 at 22:58
Dave NguyenDave Nguyen
1
$endgroup$
I've come across linear and multiple regression, SVM, random forests. Does any know of a machine learning algorithm that uses the Pearson correlation or Spearman correlation?
Best,
Dave
machine-learning correlation
machine-learning correlation
asked Jan 16 at 22:58
Dave NguyenDave Nguyen
1
asked Jan 16 at 22:58
Dave NguyenDave Nguyen
1
asked Jan 16 at 22:58
Dave NguyenDave Nguyen
1
asked Jan 16 at 22:58
Dave NguyenDave Nguyen
1
asked Jan 16 at 22:58
Dave NguyenDave Nguyen
1
1
bumped to the homepage by Community♦ 13 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♦ 13 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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$begingroup$
I do not think this exists. I suppose an algorithm could use pearson coefficients as starting coefficients, but honestly it seems like a waste of computational resources. Here are some reasons that occur to me as to why it is a bad idea:
- Pearson and Spearman correlations become decreasingly meaningful as
the number of dimensions increase. I commonly work with millions of dimensions...Spearman correlations for individual features? - In sparse matrices, these coefficients mean next to nothing as there will be only a very slight correlations between a feature and the target. Usually, it is a multi dimensional relationship that we are trying to find (lots of caveats placed here :P)
- Pearson and Spearman correlations assume certain parameters which are not usually true in ML applications ie homoscedasticity, linearity, normality, etc.
For the above and many other reasons imho it doesn't serve any purpose to use these anywhere in ML algorithms.
answered Jan 17 at 4:01
Joe BJoe B
689
$endgroup$
add a comment |
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$begingroup$
I do not think this exists. I suppose an algorithm could use pearson coefficients as starting coefficients, but honestly it seems like a waste of computational resources. Here are some reasons that occur to me as to why it is a bad idea:
- Pearson and Spearman correlations become decreasingly meaningful as
the number of dimensions increase. I commonly work with millions of dimensions...Spearman correlations for individual features? - In sparse matrices, these coefficients mean next to nothing as there will be only a very slight correlations between a feature and the target. Usually, it is a multi dimensional relationship that we are trying to find (lots of caveats placed here :P)
- Pearson and Spearman correlations assume certain parameters which are not usually true in ML applications ie homoscedasticity, linearity, normality, etc.
For the above and many other reasons imho it doesn't serve any purpose to use these anywhere in ML algorithms.
answered Jan 17 at 4:01
Joe BJoe B
689
$endgroup$
add a comment |
$begingroup$
I do not think this exists. I suppose an algorithm could use pearson coefficients as starting coefficients, but honestly it seems like a waste of computational resources. Here are some reasons that occur to me as to why it is a bad idea:
- Pearson and Spearman correlations become decreasingly meaningful as
the number of dimensions increase. I commonly work with millions of dimensions...Spearman correlations for individual features? - In sparse matrices, these coefficients mean next to nothing as there will be only a very slight correlations between a feature and the target. Usually, it is a multi dimensional relationship that we are trying to find (lots of caveats placed here :P)
- Pearson and Spearman correlations assume certain parameters which are not usually true in ML applications ie homoscedasticity, linearity, normality, etc.
For the above and many other reasons imho it doesn't serve any purpose to use these anywhere in ML algorithms.
answered Jan 17 at 4:01
Joe BJoe B
689
$endgroup$
add a comment |
$begingroup$
I do not think this exists. I suppose an algorithm could use pearson coefficients as starting coefficients, but honestly it seems like a waste of computational resources. Here are some reasons that occur to me as to why it is a bad idea:
- Pearson and Spearman correlations become decreasingly meaningful as
the number of dimensions increase. I commonly work with millions of dimensions...Spearman correlations for individual features? - In sparse matrices, these coefficients mean next to nothing as there will be only a very slight correlations between a feature and the target. Usually, it is a multi dimensional relationship that we are trying to find (lots of caveats placed here :P)
- Pearson and Spearman correlations assume certain parameters which are not usually true in ML applications ie homoscedasticity, linearity, normality, etc.
For the above and many other reasons imho it doesn't serve any purpose to use these anywhere in ML algorithms.
answered Jan 17 at 4:01
Joe BJoe B
689
$endgroup$
I do not think this exists. I suppose an algorithm could use pearson coefficients as starting coefficients, but honestly it seems like a waste of computational resources. Here are some reasons that occur to me as to why it is a bad idea:
- Pearson and Spearman correlations become decreasingly meaningful as
the number of dimensions increase. I commonly work with millions of dimensions...Spearman correlations for individual features? - In sparse matrices, these coefficients mean next to nothing as there will be only a very slight correlations between a feature and the target. Usually, it is a multi dimensional relationship that we are trying to find (lots of caveats placed here :P)
- Pearson and Spearman correlations assume certain parameters which are not usually true in ML applications ie homoscedasticity, linearity, normality, etc.
For the above and many other reasons imho it doesn't serve any purpose to use these anywhere in ML algorithms.
answered Jan 17 at 4:01
Joe BJoe B
689
answered Jan 17 at 4:01
Joe BJoe B
689
answered Jan 17 at 4:01
Joe BJoe B
689
answered Jan 17 at 4:01
Joe BJoe B
689
689
add a comment |
add a comment |
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