Package org.apache.spark.ml.feature
Class OneHotEncoderModel
- All Implemented Interfaces:
- Serializable,- org.apache.spark.internal.Logging,- OneHotEncoderBase,- Params,- HasHandleInvalid,- HasInputCol,- HasInputCols,- HasOutputCol,- HasOutputCols,- Identifiable,- MLWritable
public class OneHotEncoderModel
extends Model<OneHotEncoderModel>
implements OneHotEncoderBase, MLWritable
param:  categorySizes  Original number of categories for each feature being encoded.
                       The array contains one value for each input column, in order.
- See Also:
- 
Nested Class SummaryNested ClassesNested classes/interfaces inherited from interface org.apache.spark.internal.Loggingorg.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter
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Method SummaryModifier and TypeMethodDescriptionint[]Creates a copy of this instance with the same UID and some extra params.final BooleanParamdropLast()Whether to drop the last category in the encoded vector (default: true)Param for how to handle invalid data during transform().inputCol()Param for input column name.final StringArrayParamParam for input column names.static OneHotEncoderModelParam for output column name.final StringArrayParamParam for output column names.static MLReader<OneHotEncoderModel>read()setDropLast(boolean value) setHandleInvalid(String value) setInputCol(String value) setInputCols(String[] values) setOutputCol(String value) setOutputCols(String[] values) toString()Transforms the input dataset.transformSchema(StructType schema) Check transform validity and derive the output schema from the input schema.uid()An immutable unique ID for the object and its derivatives.write()Returns anMLWriterinstance for this ML instance.Methods inherited from class org.apache.spark.ml.Transformertransform, transform, transformMethods inherited from class org.apache.spark.ml.PipelineStageparamsMethods inherited from class java.lang.Objectequals, getClass, hashCode, notify, notifyAll, wait, wait, waitMethods inherited from interface org.apache.spark.ml.param.shared.HasHandleInvalidgetHandleInvalidMethods inherited from interface org.apache.spark.ml.param.shared.HasInputColgetInputColMethods inherited from interface org.apache.spark.ml.param.shared.HasInputColsgetInputColsMethods inherited from interface org.apache.spark.ml.param.shared.HasOutputColgetOutputColMethods inherited from interface org.apache.spark.ml.param.shared.HasOutputColsgetOutputColsMethods inherited from interface org.apache.spark.internal.LogginginitializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logBasedOnLevel, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, MDC, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, withLogContextMethods inherited from interface org.apache.spark.ml.util.MLWritablesaveMethods inherited from interface org.apache.spark.ml.feature.OneHotEncoderBasegetDropLast, getInOutCols, validateAndTransformSchemaMethods inherited from interface org.apache.spark.ml.param.Paramsclear, copyValues, defaultCopy, defaultParamMap, estimateMatadataSize, 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- 
read
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load
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handleInvalidDescription copied from interface:OneHotEncoderBaseParam 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:
- handleInvalidin interface- HasHandleInvalid
- Specified by:
- handleInvalidin interface- OneHotEncoderBase
- Returns:
- (undocumented)
 
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dropLastDescription copied from interface:OneHotEncoderBaseWhether to drop the last category in the encoded vector (default: true)- Specified by:
- dropLastin interface- OneHotEncoderBase
- Returns:
- (undocumented)
 
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outputColsDescription copied from interface:HasOutputColsParam for output column names.- Specified by:
- outputColsin interface- HasOutputCols
- Returns:
- (undocumented)
 
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outputColDescription copied from interface:HasOutputColParam for output column name.- Specified by:
- outputColin interface- HasOutputCol
- Returns:
- (undocumented)
 
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inputColsDescription copied from interface:HasInputColsParam for input column names.- Specified by:
- inputColsin interface- HasInputCols
- Returns:
- (undocumented)
 
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inputColDescription copied from interface:HasInputColParam for input column name.- Specified by:
- inputColin interface- HasInputCol
- Returns:
- (undocumented)
 
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uidDescription copied from interface:IdentifiableAn immutable unique ID for the object and its derivatives.- Specified by:
- uidin interface- Identifiable
- Returns:
- (undocumented)
 
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categorySizespublic int[] categorySizes()
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setInputCol
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setOutputCol
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setInputCols
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setOutputCols
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setDropLast
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setHandleInvalid
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transformSchemaDescription copied from class:PipelineStageCheck transform validity and derive the output schema from the input schema.We check validity for interactions between parameters during transformSchemaand raise an exception if any parameter value is invalid. Parameter value checks which do not depend on other parameters are handled byParam.validate().Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks. - Specified by:
- transformSchemain class- PipelineStage
- Parameters:
- schema- (undocumented)
- Returns:
- (undocumented)
 
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transformDescription copied from class:TransformerTransforms the input dataset.- Specified by:
- transformin class- Transformer
- Parameters:
- dataset- (undocumented)
- Returns:
- (undocumented)
 
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copyDescription copied from interface:ParamsCreates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. SeedefaultCopy().- Specified by:
- copyin interface- Params
- Specified by:
- copyin class- Model<OneHotEncoderModel>
- Parameters:
- extra- (undocumented)
- Returns:
- (undocumented)
 
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writeDescription copied from interface:MLWritableReturns anMLWriterinstance for this ML instance.- Specified by:
- writein interface- MLWritable
- Returns:
- (undocumented)
 
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toString- Specified by:
- toStringin interface- Identifiable
- Overrides:
- toStringin class- Object
 
 
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