Package org.apache.spark.ml.feature
Interface OneHotEncoderBase
- All Superinterfaces:
HasHandleInvalid
,HasInputCol
,HasInputCols
,HasOutputCol
,HasOutputCols
,Identifiable
,Params
,Serializable
- All Known Implementing Classes:
OneHotEncoder
,OneHotEncoderModel
public interface OneHotEncoderBase
extends Params, HasHandleInvalid, HasInputCol, HasInputCols, HasOutputCol, HasOutputCols
Private trait for params and common methods for OneHotEncoder and OneHotEncoderModel
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Method Summary
Modifier and TypeMethodDescriptiondropLast()
Whether to drop the last category in the encoded vector (default: true)boolean
Returns the input and output column names corresponding in pair.Param for how to handle invalid data during transform().validateAndTransformSchema
(StructType schema, boolean dropLast, boolean keepInvalid) Methods inherited from interface org.apache.spark.ml.param.shared.HasHandleInvalid
getHandleInvalid
Methods inherited from interface org.apache.spark.ml.param.shared.HasInputCol
getInputCol, inputCol
Methods inherited from interface org.apache.spark.ml.param.shared.HasInputCols
getInputCols, inputCols
Methods inherited from interface org.apache.spark.ml.param.shared.HasOutputCol
getOutputCol, outputCol
Methods inherited from interface org.apache.spark.ml.param.shared.HasOutputCols
getOutputCols, outputCols
Methods inherited from interface org.apache.spark.ml.util.Identifiable
toString, uid
Methods inherited from interface org.apache.spark.ml.param.Params
clear, copy, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn
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Method Details
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dropLast
BooleanParam dropLast()Whether to drop the last category in the encoded vector (default: true)- Returns:
- (undocumented)
-
getDropLast
boolean getDropLast() -
getInOutCols
Returns the input and output column names corresponding in pair. -
handleInvalid
Param for how to handle invalid data during transform(). Options are 'keep' (invalid data presented as an extra categorical feature) or 'error' (throw an error). Note that this Param is only used during transform; during fitting, invalid data will result in an error. Default: "error"- Specified by:
handleInvalid
in interfaceHasHandleInvalid
- Returns:
- (undocumented)
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validateAndTransformSchema
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