[MINOR] [MLLIB] [ML] [DOC] Minor doc fixes for StringIndexer and MetadataUtils
Changes: * Make Scala doc for StringIndexerInverse clearer. Also remove Scala doc from transformSchema, so that the doc is inherited. * MetadataUtils.scala: “ Helper utilities for tree-based algorithms” —> not just trees anymore CC: holdenk mengxr Author: Joseph K. Bradley <joseph@databricks.com> Closes #8679 from jkbradley/doc-fixes-1.5.
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@ -181,10 +181,10 @@ class StringIndexerModel (
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/**
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* :: Experimental ::
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* A [[Transformer]] that maps a column of string indices back to a new column of corresponding
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* string values using either the ML attributes of the input column, or if provided using the labels
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* supplied by the user.
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* All original columns are kept during transformation.
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* A [[Transformer]] that maps a column of indices back to a new column of corresponding
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* string values.
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* The index-string mapping is either from the ML attributes of the input column,
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* or from user-supplied labels (which take precedence over ML attributes).
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*
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* @see [[StringIndexer]] for converting strings into indices
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*/
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@ -202,32 +202,23 @@ class IndexToString private[ml] (
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/** @group setParam */
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def setOutputCol(value: String): this.type = set(outputCol, value)
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/**
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* Optional labels to be provided by the user, if not supplied column
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* metadata is read for labels. The default value is an empty array,
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* but the empty array is ignored and column metadata used instead.
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* @group setParam
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*/
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/** @group setParam */
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def setLabels(value: Array[String]): this.type = set(labels, value)
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/**
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* Param for array of labels.
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* Optional labels to be provided by the user.
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* Default: Empty array, in which case column metadata is used for labels.
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* Optional param for array of labels specifying index-string mapping.
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*
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* Default: Empty array, in which case [[inputCol]] metadata is used for labels.
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* @group param
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*/
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final val labels: StringArrayParam = new StringArrayParam(this, "labels",
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"array of labels, if not provided metadata from inputCol is used instead.")
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"Optional array of labels specifying index-string mapping." +
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" If not provided or if empty, then metadata from inputCol is used instead.")
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setDefault(labels, Array.empty[String])
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/**
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* Optional labels to be provided by the user, if not supplied column
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* metadata is read for labels.
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* @group getParam
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*/
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/** @group getParam */
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final def getLabels: Array[String] = $(labels)
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/** Transform the schema for the inverse transformation */
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override def transformSchema(schema: StructType): StructType = {
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val inputColName = $(inputCol)
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val inputDataType = schema(inputColName).dataType
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@ -25,7 +25,7 @@ import org.apache.spark.sql.types.StructField
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/**
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* Helper utilities for tree-based algorithms
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* Helper utilities for algorithms using ML metadata
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*/
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private[spark] object MetadataUtils {
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@ -985,17 +985,17 @@ class IndexToString(JavaTransformer, HasInputCol, HasOutputCol):
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"""
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.. note:: Experimental
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A :py:class:`Transformer` that maps a column of string indices back to a new column of
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corresponding string values using either the ML attributes of the input column, or if
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provided using the labels supplied by the user.
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All original columns are kept during transformation.
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A :py:class:`Transformer` that maps a column of indices back to a new column of
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corresponding string values.
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The index-string mapping is either from the ML attributes of the input column,
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or from user-supplied labels (which take precedence over ML attributes).
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See L{StringIndexer} for converting strings into indices.
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"""
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# a placeholder to make the labels show up in generated doc
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labels = Param(Params._dummy(), "labels",
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"Optional array of labels to be provided by the user, if not supplied or " +
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"empty, column metadata is read for labels")
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"Optional array of labels specifying index-string mapping." +
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" If not provided or if empty, then metadata from inputCol is used instead.")
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@keyword_only
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def __init__(self, inputCol=None, outputCol=None, labels=None):
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@ -1006,8 +1006,8 @@ class IndexToString(JavaTransformer, HasInputCol, HasOutputCol):
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self._java_obj = self._new_java_obj("org.apache.spark.ml.feature.IndexToString",
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self.uid)
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self.labels = Param(self, "labels",
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"Optional array of labels to be provided by the user, if not " +
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"supplied or empty, column metadata is read for labels")
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"Optional array of labels specifying index-string mapping. If not" +
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" provided or if empty, then metadata from inputCol is used instead.")
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kwargs = self.__init__._input_kwargs
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self.setParams(**kwargs)
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