How to write a predict function for mlr predict to upload in AzureML as webservice?
$begingroup$
I am trying to upload a R Model in AzureML as webservice, for the linear model like Regression I use
PredictAction <- function(inputdata){
predict(RegModel, inputdata, type="response")
}
This is working perfectly fine in Azure.
When I use mlr package for classification with predict type probability, the predict function I have to write as,
PredictAction <- function(inputdata){
require(mlr)
predict(randomForest,newdata=inputdata)
}
When calling the
publishWebService(ws, fun, name, inputSchema)
It produces an Error as
converting `inputSchema` to data frame
Error in convertArgsToAMLschema(lapply(x, class)) :
Error: data type "table" not supported
as the predict function produces a table which I don't know how to convert or modify, so I give the outputschema
publishWebService(ws, fun, name, inputSchema,outputschema)
I am not sure how to specify the outputschema
https://cran.r-project.org/web/packages/AzureML/AzureML.pdf
outputschema is a list,
the predict function from mlr produces the output of class
class(pred_randomForest)
"PredictionClassif" "Prediction"
and the data output is a dataframe
class(pred_randomForest$data)
"data.frame"
I am seeking help on the syntax for outputschema in publishWebService function, or whether I have to add any other arguments of the function, Thanks in advance
machine-learning r azure-ml
New contributor
$endgroup$
add a comment |
$begingroup$
I am trying to upload a R Model in AzureML as webservice, for the linear model like Regression I use
PredictAction <- function(inputdata){
predict(RegModel, inputdata, type="response")
}
This is working perfectly fine in Azure.
When I use mlr package for classification with predict type probability, the predict function I have to write as,
PredictAction <- function(inputdata){
require(mlr)
predict(randomForest,newdata=inputdata)
}
When calling the
publishWebService(ws, fun, name, inputSchema)
It produces an Error as
converting `inputSchema` to data frame
Error in convertArgsToAMLschema(lapply(x, class)) :
Error: data type "table" not supported
as the predict function produces a table which I don't know how to convert or modify, so I give the outputschema
publishWebService(ws, fun, name, inputSchema,outputschema)
I am not sure how to specify the outputschema
https://cran.r-project.org/web/packages/AzureML/AzureML.pdf
outputschema is a list,
the predict function from mlr produces the output of class
class(pred_randomForest)
"PredictionClassif" "Prediction"
and the data output is a dataframe
class(pred_randomForest$data)
"data.frame"
I am seeking help on the syntax for outputschema in publishWebService function, or whether I have to add any other arguments of the function, Thanks in advance
machine-learning r azure-ml
New contributor
$endgroup$
add a comment |
$begingroup$
I am trying to upload a R Model in AzureML as webservice, for the linear model like Regression I use
PredictAction <- function(inputdata){
predict(RegModel, inputdata, type="response")
}
This is working perfectly fine in Azure.
When I use mlr package for classification with predict type probability, the predict function I have to write as,
PredictAction <- function(inputdata){
require(mlr)
predict(randomForest,newdata=inputdata)
}
When calling the
publishWebService(ws, fun, name, inputSchema)
It produces an Error as
converting `inputSchema` to data frame
Error in convertArgsToAMLschema(lapply(x, class)) :
Error: data type "table" not supported
as the predict function produces a table which I don't know how to convert or modify, so I give the outputschema
publishWebService(ws, fun, name, inputSchema,outputschema)
I am not sure how to specify the outputschema
https://cran.r-project.org/web/packages/AzureML/AzureML.pdf
outputschema is a list,
the predict function from mlr produces the output of class
class(pred_randomForest)
"PredictionClassif" "Prediction"
and the data output is a dataframe
class(pred_randomForest$data)
"data.frame"
I am seeking help on the syntax for outputschema in publishWebService function, or whether I have to add any other arguments of the function, Thanks in advance
machine-learning r azure-ml
New contributor
$endgroup$
I am trying to upload a R Model in AzureML as webservice, for the linear model like Regression I use
PredictAction <- function(inputdata){
predict(RegModel, inputdata, type="response")
}
This is working perfectly fine in Azure.
When I use mlr package for classification with predict type probability, the predict function I have to write as,
PredictAction <- function(inputdata){
require(mlr)
predict(randomForest,newdata=inputdata)
}
When calling the
publishWebService(ws, fun, name, inputSchema)
It produces an Error as
converting `inputSchema` to data frame
Error in convertArgsToAMLschema(lapply(x, class)) :
Error: data type "table" not supported
as the predict function produces a table which I don't know how to convert or modify, so I give the outputschema
publishWebService(ws, fun, name, inputSchema,outputschema)
I am not sure how to specify the outputschema
https://cran.r-project.org/web/packages/AzureML/AzureML.pdf
outputschema is a list,
the predict function from mlr produces the output of class
class(pred_randomForest)
"PredictionClassif" "Prediction"
and the data output is a dataframe
class(pred_randomForest$data)
"data.frame"
I am seeking help on the syntax for outputschema in publishWebService function, or whether I have to add any other arguments of the function, Thanks in advance
machine-learning r azure-ml
machine-learning r azure-ml
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