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32 lines
1.0 KiB
Transact-SQL
32 lines
1.0 KiB
Transact-SQL
USE sqlr;
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GO
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/* Create procedure for scoring using the decision tree model */
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create or alter procedure predict_iris_species (@model varchar(100))
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as
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begin
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declare @rx_model varbinary(max) = (select model from iris_models where model_name = @model);
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-- Predict based on the specified model:
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exec sp_execute_external_script
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@language = N'R'
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, @script = N'
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# Unserialize model from SQL Server
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irismodel<-unserialize(rx_model);
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# Predict species for new data using rxDTree model
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OutputDataSet <-rxPredict(irismodel, iris_rx_data, extraVarsToWrite = c("Species", "id"));
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'
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, @input_data_1 = N'
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select id, "Sepal.Length", "Sepal.Width", "Petal.Length", "Petal.Width", "Species"
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from iris_data'
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, @input_data_1_name = N'iris_rx_data'
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, @params = N'@rx_model varbinary(max)'
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, @rx_model = @rx_model
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with result sets ( ("setosa_Pred" float, "versicolor_Pred" float, "virginica_Pred" float, "Species.Actual" varchar(100), "id" int));
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end;
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go
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/* Test scoring of model */
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exec predict_iris_species 'iris.dtree';
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go
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