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How to write a predict function for mlr predict to upload in AzureML as webservice?
The Next CEO of Stack Overflow2019 Community Moderator ElectionHow to predict probabilities in xgboost?How do write the following piece of code in R?How to interpret agglomerative coefficient agnes() function?Best way for data preparation to have accurate predictionHow to calculate growth function for a threshold functionReLU activation function outputs HUGE numbersHow to predict a group of events using machine learning?regsubsets function in R for feature selectionHow to resolve Error in predict.rpart(fitTree, data = hypo_mode, type = “class”) : Invalid prediction for “rpart” object?How to approach a machine learning problem?
$begingroup$
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
New contributor
New contributor
New contributor
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