Package org.apache.spark.ml.feature
Class VectorAssembler
Object
org.apache.spark.ml.PipelineStage
org.apache.spark.ml.Transformer
org.apache.spark.ml.feature.VectorAssembler
- All Implemented Interfaces:
- Serializable,- org.apache.spark.internal.Logging,- Params,- HasHandleInvalid,- HasInputCols,- HasOutputCol,- DefaultParamsWritable,- Identifiable,- MLWritable
public class VectorAssembler
extends Transformer
implements HasInputCols, HasOutputCol, HasHandleInvalid, DefaultParamsWritable
A feature transformer that merges multiple columns into a vector column.
 
This requires one pass over the entire dataset. In case we need to infer column lengths from the data we require an additional call to the 'first' Dataset method, see 'handleInvalid' parameter.
- See Also:
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Nested Class SummaryNested 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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Constructor SummaryConstructors
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Method SummaryModifier and TypeMethodDescriptionCreates a copy of this instance with the same UID and some extra params.Param for how to handle invalid data (NULL values).final StringArrayParamParam for input column names.static VectorAssemblerParam for output column name.static MLReader<T>read()setHandleInvalid(String value) setInputCols(String[] value) setOutputCol(String value) 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.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.util.DefaultParamsWritablewriteMethods inherited from interface org.apache.spark.ml.param.shared.HasHandleInvalidgetHandleInvalidMethods 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.internal.LogginginitializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logBasedOnLevel, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, org$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.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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Constructor Details- 
VectorAssembler
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VectorAssemblerpublic VectorAssembler()
 
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Method Details- 
load
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read
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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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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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setInputCols
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setOutputCol
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setHandleInvalid
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handleInvalidParam for how to handle invalid data (NULL values). Options are 'skip' (filter out rows with invalid data), 'error' (throw an error), or 'keep' (return relevant number of NaN in the output). Column lengths are taken from the size of ML Attribute Group, which can be set usingVectorSizeHintin a pipeline beforeVectorAssembler. Column lengths can also be inferred from first rows of the data since it is safe to do so but only in case of 'error' or 'skip'. Default: "error"- Specified by:
- handleInvalidin interface- HasHandleInvalid
- 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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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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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- Transformer
- Parameters:
- extra- (undocumented)
- Returns:
- (undocumented)
 
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toString- Specified by:
- toStringin interface- Identifiable
- Overrides:
- toStringin class- Object
 
 
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