| title | concat function (MicrosoftML) | |||
|---|---|---|---|---|
| description | Combines several columns into a single vector-valued column (MicrosoftML). | |||
| author | rothja | |||
| ms.author | jroth | |||
| ms.date | 07/15/2019 | |||
| ms.service | sql | |||
| ms.subservice | machine-learning | |||
| ms.topic | reference | |||
| keywords |
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| monikerRange | >=sql-server-2016||>=sql-server-linux-ver15 |
Combines several columns into a single vector-valued column.
concat(vars, ...)
A named list of character vectors of input variable names and the name of the output variable. Note that all the input variables must be of the same type. It is possible to produce multiple output columns with the concatenation transform. In this case, you need to use a list of vectors to define a one-to-one mapping between input and output variables. For example, to concatenate columns InNameA and InNameB into column OutName1 and also columns InNameC and InNameD into column OutName2, use the list: (list(OutName1 = c(InNameA, InNameB), outName2 = c(InNameC, InNameD)))
Additional arguments sent to the compute engine
concat creates a single vector-valued column from multiple
columns. It can be performed on data before training a model. The concatenation
can significantly speed up the processing of data when the number of columns
is as large as hundreds to thousands.
A maml object defining the concatenation transform.
Microsoft Corporation Microsoft Technical Support
featurizeText, categorical, categoricalHash, rxFastTrees, rxFastForest, rxNeuralNet, rxOneClassSvm, rxLogisticRegression.
testObs <- rnorm(nrow(iris)) > 0
testIris <- iris[testObs,]
trainIris <- iris[!testObs,]
multiLogitOut <- rxLogisticRegression(
formula = Species~Features, type = "multiClass", data = trainIris,
mlTransforms = list(concat(vars = list(
Features = c("Sepal.Length", "Sepal.Width", "Petal.Length", "Petal.Width")
))))
summary(multiLogitOut)