Is it possible to fit a model to a vector outcome?
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I have a data set with 60 features. 10 of these features are target variables in 1/0 format.
Using caret and e.g. random forest I could fit 10 separate models on each of the 10 target features.
My question is, is it possible to fit a model to a vector?
Suppose for the e.g. 1st observation the ten target variables are c(1,1,1,0,1,0,0,0,0,1). I could create a model for each where the outcome is either 0 or 1.
My question is, is there some way to fit a model on a vector of outcomes so that I only need to fit one model not 10?
r r-caret
asked Nov 6 at 23:54
Doug Fir
5,2222680147
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up vote
0
down vote
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I have a data set with 60 features. 10 of these features are target variables in 1/0 format.
Using caret and e.g. random forest I could fit 10 separate models on each of the 10 target features.
My question is, is it possible to fit a model to a vector?
Suppose for the e.g. 1st observation the ten target variables are c(1,1,1,0,1,0,0,0,0,1). I could create a model for each where the outcome is either 0 or 1.
My question is, is there some way to fit a model on a vector of outcomes so that I only need to fit one model not 10?
r r-caret
asked Nov 6 at 23:54
Doug Fir
5,2222680147
As I understand your sole aim is to make model fitting more concise, and to actually still fit 10 separate models, right? In that case, I guess the answer is negative asyis supposed, when usingtrain, to be "A numeric or factor vector containing the outcome for each sample.". If you wanted to do a kind of multivariate model, you could transform your vector into a factor. But in that case there would be some serious problems when the vector is long enough.
– Julius Vainora
Nov 7 at 0:13
2
Really a methodological question, but yes, you can have a matrix on hte LHS or regression functions.
– 42-
Nov 7 at 0:19
This is called multi-label classification. It can be done in mlr, take a look at this. I am not sure, but think it can not be done in caret.
– missuse
Nov 7 at 12:56
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
I have a data set with 60 features. 10 of these features are target variables in 1/0 format.
Using caret and e.g. random forest I could fit 10 separate models on each of the 10 target features.
My question is, is it possible to fit a model to a vector?
Suppose for the e.g. 1st observation the ten target variables are c(1,1,1,0,1,0,0,0,0,1). I could create a model for each where the outcome is either 0 or 1.
My question is, is there some way to fit a model on a vector of outcomes so that I only need to fit one model not 10?
r r-caret
asked Nov 6 at 23:54
Doug Fir
5,2222680147
I have a data set with 60 features. 10 of these features are target variables in 1/0 format.
Using caret and e.g. random forest I could fit 10 separate models on each of the 10 target features.
My question is, is it possible to fit a model to a vector?
Suppose for the e.g. 1st observation the ten target variables are c(1,1,1,0,1,0,0,0,0,1). I could create a model for each where the outcome is either 0 or 1.
My question is, is there some way to fit a model on a vector of outcomes so that I only need to fit one model not 10?
r r-caret
r r-caret
asked Nov 6 at 23:54
Doug Fir
5,2222680147
asked Nov 6 at 23:54
Doug Fir
5,2222680147
asked Nov 6 at 23:54
Doug Fir
5,2222680147
asked Nov 6 at 23:54
Doug Fir
5,2222680147
asked Nov 6 at 23:54
Doug Fir
5,2222680147
5,2222680147
As I understand your sole aim is to make model fitting more concise, and to actually still fit 10 separate models, right? In that case, I guess the answer is negative asyis supposed, when usingtrain, to be "A numeric or factor vector containing the outcome for each sample.". If you wanted to do a kind of multivariate model, you could transform your vector into a factor. But in that case there would be some serious problems when the vector is long enough.
– Julius Vainora
Nov 7 at 0:13
2
Really a methodological question, but yes, you can have a matrix on hte LHS or regression functions.
– 42-
Nov 7 at 0:19
This is called multi-label classification. It can be done in mlr, take a look at this. I am not sure, but think it can not be done in caret.
– missuse
Nov 7 at 12:56
add a comment |
As I understand your sole aim is to make model fitting more concise, and to actually still fit 10 separate models, right? In that case, I guess the answer is negative asyis supposed, when usingtrain, to be "A numeric or factor vector containing the outcome for each sample.". If you wanted to do a kind of multivariate model, you could transform your vector into a factor. But in that case there would be some serious problems when the vector is long enough.
– Julius Vainora
Nov 7 at 0:13
2
Really a methodological question, but yes, you can have a matrix on hte LHS or regression functions.
– 42-
Nov 7 at 0:19
This is called multi-label classification. It can be done in mlr, take a look at this. I am not sure, but think it can not be done in caret.
– missuse
Nov 7 at 12:56
As I understand your sole aim is to make model fitting more concise, and to actually still fit 10 separate models, right? In that case, I guess the answer is negative as
y is supposed, when using train, to be "A numeric or factor vector containing the outcome for each sample.". If you wanted to do a kind of multivariate model, you could transform your vector into a factor. But in that case there would be some serious problems when the vector is long enough.– Julius Vainora
Nov 7 at 0:13
As I understand your sole aim is to make model fitting more concise, and to actually still fit 10 separate models, right? In that case, I guess the answer is negative as
y is supposed, when using train, to be "A numeric or factor vector containing the outcome for each sample.". If you wanted to do a kind of multivariate model, you could transform your vector into a factor. But in that case there would be some serious problems when the vector is long enough.– Julius Vainora
Nov 7 at 0:13
2
2
Really a methodological question, but yes, you can have a matrix on hte LHS or regression functions.
– 42-
Nov 7 at 0:19
Really a methodological question, but yes, you can have a matrix on hte LHS or regression functions.
– 42-
Nov 7 at 0:19
This is called multi-label classification. It can be done in mlr, take a look at this. I am not sure, but think it can not be done in caret.
– missuse
Nov 7 at 12:56
This is called multi-label classification. It can be done in mlr, take a look at this. I am not sure, but think it can not be done in caret.
– missuse
Nov 7 at 12:56
add a comment |
1 Answer
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votes
up vote
0
down vote
accepted
No, caret does not support multiple outputs. See e.g. here (https://github.com/topepo/caret/issues/466#issuecomment-317527852) where the author of caret confirms this.
answered Nov 11 at 8:40
Gertjan Verhoeven
496
add a comment |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
accepted
No, caret does not support multiple outputs. See e.g. here (https://github.com/topepo/caret/issues/466#issuecomment-317527852) where the author of caret confirms this.
answered Nov 11 at 8:40
Gertjan Verhoeven
496
add a comment |
up vote
0
down vote
accepted
No, caret does not support multiple outputs. See e.g. here (https://github.com/topepo/caret/issues/466#issuecomment-317527852) where the author of caret confirms this.
answered Nov 11 at 8:40
Gertjan Verhoeven
496
add a comment |
up vote
0
down vote
accepted
up vote
0
down vote
accepted
No, caret does not support multiple outputs. See e.g. here (https://github.com/topepo/caret/issues/466#issuecomment-317527852) where the author of caret confirms this.
answered Nov 11 at 8:40
Gertjan Verhoeven
496
No, caret does not support multiple outputs. See e.g. here (https://github.com/topepo/caret/issues/466#issuecomment-317527852) where the author of caret confirms this.
answered Nov 11 at 8:40
Gertjan Verhoeven
496
answered Nov 11 at 8:40
Gertjan Verhoeven
496
answered Nov 11 at 8:40
Gertjan Verhoeven
496
answered Nov 11 at 8:40
Gertjan Verhoeven
496
496
add a comment |
add a comment |
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As I understand your sole aim is to make model fitting more concise, and to actually still fit 10 separate models, right? In that case, I guess the answer is negative as
yis supposed, when usingtrain, to be "A numeric or factor vector containing the outcome for each sample.". If you wanted to do a kind of multivariate model, you could transform your vector into a factor. But in that case there would be some serious problems when the vector is long enough.– Julius Vainora
Nov 7 at 0:13
2
Really a methodological question, but yes, you can have a matrix on hte LHS or regression functions.
– 42-
Nov 7 at 0:19
This is called multi-label classification. It can be done in mlr, take a look at this. I am not sure, but think it can not be done in caret.
– missuse
Nov 7 at 12:56