rxFeaturize: Data Transformation for RevoScaleR data sources

Artikkeli
02/28/2023

Transforms data from an input data set to an output data set.

Usage

  rxFeaturize(data, outData = NULL, overwrite = FALSE, dataThreads = NULL,
    randomSeed = NULL, maxSlots = 5000, mlTransforms = NULL,
    mlTransformVars = NULL, rowSelection = NULL, transforms = NULL,
    transformObjects = NULL, transformFunc = NULL, transformVars = NULL,
    transformPackages = NULL, transformEnvir = NULL,
    blocksPerRead = rxGetOption("blocksPerRead"),
    reportProgress = rxGetOption("reportProgress"), verbose = 1,
    computeContext = rxGetOption("computeContext"), ...)

Arguments

`data`

A RevoScaleR data source object, a data frame, or the path to a .xdf file.

`outData`

Output text or xdf file name or an RxDataSource with write capabilities in which to store transformed data. If NULL, a data frame is returned. The default value is NULL.

`overwrite`

If TRUE, an existing outData is overwritten; if FALSE an existing outData is not overwritten. The default value is /codeFALSE.

`dataThreads`

An integer specifying the desired degree of parallelism in the data pipeline. If NULL, the number of threads used is determined internally. The default value is NULL.

`randomSeed`

Specifies the random seed. The default value is NULL.

`maxSlots`

Max slots to return for vector valued columns (<=0 to return all).

`mlTransforms`

Specifies a list of MicrosoftML transforms to be performed on the data before training or NULL if no transforms are to be performed. See featurizeText, categorical, and categoricalHash, for transformations that are supported. These transformations are performed after any specified R transformations. The default value is NULL.

`mlTransformVars`

Specifies a character vector of variable names to be used in mlTransforms or NULL if none are to be used. The default value is NULL.

`rowSelection`

Specifies the rows (observations) from the data set that are to be used by the model with the name of a logical variable from the data set (in quotes) or with a logical expression using variables in the data set. For example, rowSelection = "old" will only use observations in which the value of the variable old is TRUE. rowSelection = (age > 20) & (age < 65) & (log(income) > 10) only uses observations in which the value of the age variable is between 20 and 65 and the value of the log of the income variable is greater than 10. The row selection is performed after processing any data transformations (see the arguments transforms or transformFunc). As with all expressions, rowSelection can be defined outside of the function call using the expression function.

`transforms`

An expression of the form list(name = expression, ``...) that represents the first round of variable transformations. As with all expressions, transforms (or rowSelection) can be defined outside of the function call using the expression function. The default value is NULL.

`transformObjects`

A named list that contains objects that can be referenced by transforms, transformsFunc, and rowSelection. The default value is NULL.

`transformFunc`

The variable transformation function. See rxTransform for details. The default value is NULL.

`transformVars`

A character vector of input data set variables needed for the transformation function. See rxTransform for details. The default value is NULL.

`transformPackages`

A character vector specifying additional R packages (outside of those specified in rxGetOption("transformPackages")) to be made available and preloaded for use in variable transformation functions. For example, those explicitly defined in RevoScaleR functions via their transforms and transformFunc arguments or those defined implicitly via their formula or rowSelection arguments. The transformPackages argument may also be NULL, indicating that no packages outside rxGetOption("transformPackages") are preloaded. The default value is NULL.

`transformEnvir`

A user-defined environment to serve as a parent to all environments developed internally and used for variable data transformation. If transformEnvir = NULL, a new "hash" environment with parent baseenv() is used instead The default value is NULL.

`blocksPerRead`

Specifies the number of blocks to read for each chunk of data read from the data source.

`reportProgress`

An integer value that specifies the level of reporting on the row processing progress:

0: no progress is reported.
1: the number of processed rows is printed and updated.
2: rows processed and timings are reported.
3: rows processed and all timings are reported.
The default value is 1.

`verbose`

An integer value that specifies the amount of output wanted. If 0, no verbose output is printed during calculations. Integer values from 1 to 4 provide increasing amounts of information. The default value is 1.

`computeContext`

Sets the context in which computations are executed, specified with a valid RxComputeContext. Currently local and RxInSqlServer compute contexts are supported.

`...`

Additional arguments to be passed directly to the Microsoft Compute Engine.

Value

A data frame or an RxDataSource object representing the created output data.

Author(s)

Microsoft Corporation Microsoft Technical Support

Examples


 # rxFeaturize basically allows you to access data from the MicrosoftML transforms
 # In this example we'll look at getting the output of the categorical transform

 # Create the data
 categoricalData <- data.frame(
   placesVisited = c(
     "London",
     "Brunei",
     "London",
     "Paris",
     "Seria"
   ),
   stringsAsFactors = FALSE
 )

 # Invoke the categorical transform
 categorized <- rxFeaturize(
   data = categoricalData,
   mlTransforms = list(categorical(vars = c(xDataCat = "placesVisited")))
 )

 # Now let's look at the data
 categorized

Jaa