Bases: mmlspark.Utils.ComplexParamsMixin, pyspark.ml.util.JavaMLReadable, pyspark.ml.util.JavaMLWritable, pyspark.ml.wrapper.JavaTransformer
A fast vector assembler. The columns given must be ordered such that
categorical columns come first. Otherwise, Spark learners will give
categorical attributes to the wrong index. The assembler does not keep
spurious numeric data which can significantly slow down computations
when there are millions of columns.
To use this FastVectorAssemble you must import the
org.apache.spark.ml.feature package.
| Parameters: |
- inputCols (list) – input column names
- outputCol (str) – output column name (default: [self.uid]__output)
|
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getInputCols()[source]
| Returns: | input column names |
|---|
| Return type: | list |
|---|
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static
getJavaPackage()[source]
Returns package name String.
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getOutputCol()[source]
| Returns: | output column name (default: [self.uid]__output) |
|---|
| Return type: | str |
|---|
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classmethod
read()[source]
Returns an MLReader instance for this class.
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setInputCols(value)[source]
| Parameters: | inputCols (list) – input column names |
|---|
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setOutputCol(value)[source]
| Parameters: | outputCol (str) – output column name (default: [self.uid]__output) |
|---|
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setParams(inputCols=None, outputCol=None)[source]
Set the (keyword only) parameters
| Parameters: |
- inputCols (list) – input column names
- outputCol (str) – output column name (default: [self.uid]__output)
|
|---|