training one SVM model for predicting more than one response variableVisualizing Support Vector Machines (SVM) with Multiple Explanatory VariablesHow synthetic sampling of data helps classifier to predict better result?Classification followed by regression to handle response variable that is usually zeroHow do I compare coefficients from my glm when I have more than one factor variable in my formula?Muti-Output Decision tree with classification and regression in outputIs it possible for a ML model to perform worse than random classification?Meaning of “TRUE” column in R RandomForest output for Importance()?one single value target variablePoor performance of SVM after training for rare events
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training one SVM model for predicting more than one response variable
Visualizing Support Vector Machines (SVM) with Multiple Explanatory VariablesHow synthetic sampling of data helps classifier to predict better result?Classification followed by regression to handle response variable that is usually zeroHow do I compare coefficients from my glm when I have more than one factor variable in my formula?Muti-Output Decision tree with classification and regression in outputIs it possible for a ML model to perform worse than random classification?Meaning of “TRUE” column in R RandomForest output for Importance()?one single value target variablePoor performance of SVM after training for rare events
$begingroup$
Please I want to know if there is any SVM R package that can handle more than one response variable (y) at a time. that is to train one model for predicting more than one response variable. it could be regression or multi class classification problem.
Thanks for your help
machine-learning r algorithms
asked Feb 25 '15 at 18:28
Aminu SuleimanAminu Suleiman
111
$endgroup$
add a comment |
$begingroup$
Please I want to know if there is any SVM R package that can handle more than one response variable (y) at a time. that is to train one model for predicting more than one response variable. it could be regression or multi class classification problem.
Thanks for your help
machine-learning r algorithms
asked Feb 25 '15 at 18:28
Aminu SuleimanAminu Suleiman
111
$endgroup$
2
$begingroup$
Just a little thought here. Why don't you just train one SVM for each response variable?
$endgroup$
– Pablo Suau
Feb 27 '15 at 9:15
$begingroup$
I second @PabloSuau's thought. Many packages have the capability to train multi-class classifiers, but often what's happening under the hood is that n binary classifiers are trained, and these are used individually to make predictions for each class. The SO question here also seems relevant: stackoverflow.com/questions/22009871/…
$endgroup$
– kylerthecreator
Jun 29 '15 at 19:32
add a comment |
$begingroup$
Please I want to know if there is any SVM R package that can handle more than one response variable (y) at a time. that is to train one model for predicting more than one response variable. it could be regression or multi class classification problem.
Thanks for your help
machine-learning r algorithms
asked Feb 25 '15 at 18:28
Aminu SuleimanAminu Suleiman
111
$endgroup$
Please I want to know if there is any SVM R package that can handle more than one response variable (y) at a time. that is to train one model for predicting more than one response variable. it could be regression or multi class classification problem.
Thanks for your help
machine-learning r algorithms
machine-learning r algorithms
asked Feb 25 '15 at 18:28
Aminu SuleimanAminu Suleiman
111
asked Feb 25 '15 at 18:28
Aminu SuleimanAminu Suleiman
111
asked Feb 25 '15 at 18:28
Aminu SuleimanAminu Suleiman
111
asked Feb 25 '15 at 18:28
Aminu SuleimanAminu Suleiman
111
asked Feb 25 '15 at 18:28
Aminu SuleimanAminu Suleiman
111
111
2
$begingroup$
Just a little thought here. Why don't you just train one SVM for each response variable?
$endgroup$
– Pablo Suau
Feb 27 '15 at 9:15
$begingroup$
I second @PabloSuau's thought. Many packages have the capability to train multi-class classifiers, but often what's happening under the hood is that n binary classifiers are trained, and these are used individually to make predictions for each class. The SO question here also seems relevant: stackoverflow.com/questions/22009871/…
$endgroup$
– kylerthecreator
Jun 29 '15 at 19:32
add a comment |
2
$begingroup$
Just a little thought here. Why don't you just train one SVM for each response variable?
$endgroup$
– Pablo Suau
Feb 27 '15 at 9:15
$begingroup$
I second @PabloSuau's thought. Many packages have the capability to train multi-class classifiers, but often what's happening under the hood is that n binary classifiers are trained, and these are used individually to make predictions for each class. The SO question here also seems relevant: stackoverflow.com/questions/22009871/…
$endgroup$
– kylerthecreator
Jun 29 '15 at 19:32
2
2
$begingroup$
Just a little thought here. Why don't you just train one SVM for each response variable?
$endgroup$
– Pablo Suau
Feb 27 '15 at 9:15
$begingroup$
Just a little thought here. Why don't you just train one SVM for each response variable?
$endgroup$
– Pablo Suau
Feb 27 '15 at 9:15
$begingroup$
I second @PabloSuau's thought. Many packages have the capability to train multi-class classifiers, but often what's happening under the hood is that n binary classifiers are trained, and these are used individually to make predictions for each class. The SO question here also seems relevant: stackoverflow.com/questions/22009871/…
$endgroup$
– kylerthecreator
Jun 29 '15 at 19:32
$begingroup$
I second @PabloSuau's thought. Many packages have the capability to train multi-class classifiers, but often what's happening under the hood is that n binary classifiers are trained, and these are used individually to make predictions for each class. The SO question here also seems relevant: stackoverflow.com/questions/22009871/…
$endgroup$
– kylerthecreator
Jun 29 '15 at 19:32
add a comment |
3 Answers
3
active
oldest
votes
$begingroup$
e1071 is a highly popular and therefore safe solution for this purpose.
But if data starts to get bigger I would go with classyfire. It's a quite fresh package built on e1071. It is highly optimized and have some other nice feature too. In my experience it produced similar results to e1071 but with a much faster speed as it was able to utilize all 4 core of my processor.
edited yesterday
KT12
648
answered Jul 27 '15 at 21:32
ViktorViktor
3841213
$endgroup$
add a comment |
$begingroup$
Check out the e1071 package, here is the manual http://cran.r-project.org/web/packages/e1071/e1071.pdf
answered Feb 27 '15 at 8:13
coulminercoulminer
183
$endgroup$
add a comment |
$begingroup$
Clarification: are we talking about multiclass
https://en.wikipedia.org/wiki/Multiclass_classification
or multilabel?
https://en.wikipedia.org/wiki/Multi-label_classification
answered Jul 29 '15 at 10:37
kpbkpb
36913
$endgroup$
add a comment |
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3 Answers
3
active
oldest
votes
3 Answers
3
active
oldest
votes
active
oldest
votes
active
oldest
votes
$begingroup$
e1071 is a highly popular and therefore safe solution for this purpose.
But if data starts to get bigger I would go with classyfire. It's a quite fresh package built on e1071. It is highly optimized and have some other nice feature too. In my experience it produced similar results to e1071 but with a much faster speed as it was able to utilize all 4 core of my processor.
edited yesterday
KT12
648
answered Jul 27 '15 at 21:32
ViktorViktor
3841213
$endgroup$
add a comment |
$begingroup$
e1071 is a highly popular and therefore safe solution for this purpose.
But if data starts to get bigger I would go with classyfire. It's a quite fresh package built on e1071. It is highly optimized and have some other nice feature too. In my experience it produced similar results to e1071 but with a much faster speed as it was able to utilize all 4 core of my processor.
edited yesterday
KT12
648
answered Jul 27 '15 at 21:32
ViktorViktor
3841213
$endgroup$
add a comment |
$begingroup$
e1071 is a highly popular and therefore safe solution for this purpose.
But if data starts to get bigger I would go with classyfire. It's a quite fresh package built on e1071. It is highly optimized and have some other nice feature too. In my experience it produced similar results to e1071 but with a much faster speed as it was able to utilize all 4 core of my processor.
edited yesterday
KT12
648
answered Jul 27 '15 at 21:32
ViktorViktor
3841213
$endgroup$
e1071 is a highly popular and therefore safe solution for this purpose.
But if data starts to get bigger I would go with classyfire. It's a quite fresh package built on e1071. It is highly optimized and have some other nice feature too. In my experience it produced similar results to e1071 but with a much faster speed as it was able to utilize all 4 core of my processor.
edited yesterday
KT12
648
answered Jul 27 '15 at 21:32
ViktorViktor
3841213
edited yesterday
KT12
648
edited yesterday
KT12
648
edited yesterday
KT12
648
648
answered Jul 27 '15 at 21:32
ViktorViktor
3841213
answered Jul 27 '15 at 21:32
ViktorViktor
3841213
answered Jul 27 '15 at 21:32
ViktorViktor
3841213
3841213
add a comment |
add a comment |
$begingroup$
Check out the e1071 package, here is the manual http://cran.r-project.org/web/packages/e1071/e1071.pdf
answered Feb 27 '15 at 8:13
coulminercoulminer
183
$endgroup$
add a comment |
$begingroup$
Check out the e1071 package, here is the manual http://cran.r-project.org/web/packages/e1071/e1071.pdf
answered Feb 27 '15 at 8:13
coulminercoulminer
183
$endgroup$
add a comment |
$begingroup$
Check out the e1071 package, here is the manual http://cran.r-project.org/web/packages/e1071/e1071.pdf
answered Feb 27 '15 at 8:13
coulminercoulminer
183
$endgroup$
Check out the e1071 package, here is the manual http://cran.r-project.org/web/packages/e1071/e1071.pdf
answered Feb 27 '15 at 8:13
coulminercoulminer
183
answered Feb 27 '15 at 8:13
coulminercoulminer
183
answered Feb 27 '15 at 8:13
coulminercoulminer
183
answered Feb 27 '15 at 8:13
coulminercoulminer
183
183
add a comment |
add a comment |
$begingroup$
Clarification: are we talking about multiclass
https://en.wikipedia.org/wiki/Multiclass_classification
or multilabel?
https://en.wikipedia.org/wiki/Multi-label_classification
answered Jul 29 '15 at 10:37
kpbkpb
36913
$endgroup$
add a comment |
$begingroup$
Clarification: are we talking about multiclass
https://en.wikipedia.org/wiki/Multiclass_classification
or multilabel?
https://en.wikipedia.org/wiki/Multi-label_classification
answered Jul 29 '15 at 10:37
kpbkpb
36913
$endgroup$
add a comment |
$begingroup$
Clarification: are we talking about multiclass
https://en.wikipedia.org/wiki/Multiclass_classification
or multilabel?
https://en.wikipedia.org/wiki/Multi-label_classification
answered Jul 29 '15 at 10:37
kpbkpb
36913
$endgroup$
Clarification: are we talking about multiclass
https://en.wikipedia.org/wiki/Multiclass_classification
or multilabel?
https://en.wikipedia.org/wiki/Multi-label_classification
answered Jul 29 '15 at 10:37
kpbkpb
36913
answered Jul 29 '15 at 10:37
kpbkpb
36913
answered Jul 29 '15 at 10:37
kpbkpb
36913
answered Jul 29 '15 at 10:37
kpbkpb
36913
36913
add a comment |
add a comment |
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$begingroup$
Just a little thought here. Why don't you just train one SVM for each response variable?
$endgroup$
– Pablo Suau
Feb 27 '15 at 9:15
$begingroup$
I second @PabloSuau's thought. Many packages have the capability to train multi-class classifiers, but often what's happening under the hood is that n binary classifiers are trained, and these are used individually to make predictions for each class. The SO question here also seems relevant: stackoverflow.com/questions/22009871/…
$endgroup$
– kylerthecreator
Jun 29 '15 at 19:32