Package org.apache.spark.ml.feature
Class StandardScaler
- All Implemented Interfaces:
Serializable,org.apache.spark.internal.Logging,StandardScalerParams,Params,HasInputCol,HasOutputCol,DefaultParamsWritable,Identifiable,MLWritable
public class StandardScaler
extends Estimator<StandardScalerModel>
implements StandardScalerParams, DefaultParamsWritable
Standardizes features by removing the mean and scaling to unit variance using column summary
statistics on the samples in the training set.
The "unit std" is computed using the corrected sample standard deviation, which is computed as the square root of the unbiased sample variance.
- See Also:
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Nested Class Summary
Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging
org.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter -
Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionCreates a copy of this instance with the same UID and some extra params.Fits a model to the input data.inputCol()Param for input column name.static StandardScalerParam for output column name.static MLReader<T>read()setInputCol(String value) setOutputCol(String value) setWithMean(boolean value) setWithStd(boolean value) 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.withMean()Whether to center the data with mean before scaling.withStd()Whether to scale the data to unit standard deviation.Methods inherited from class org.apache.spark.ml.PipelineStage
paramsMethods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitMethods inherited from interface org.apache.spark.ml.util.DefaultParamsWritable
writeMethods inherited from interface org.apache.spark.ml.param.shared.HasInputCol
getInputColMethods inherited from interface org.apache.spark.ml.param.shared.HasOutputCol
getOutputColMethods inherited from interface org.apache.spark.ml.util.Identifiable
toStringMethods inherited from interface org.apache.spark.internal.Logging
initializeForcefully, 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.MLWritable
saveMethods inherited from interface org.apache.spark.ml.param.Params
clear, copyValues, defaultCopy, defaultParamMap, estimateMatadataSize, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwnMethods inherited from interface org.apache.spark.ml.feature.StandardScalerParams
getWithMean, getWithStd, validateAndTransformSchema
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Constructor Details
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StandardScaler
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StandardScaler
public StandardScaler()
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Method Details
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load
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read
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withMean
Description copied from interface:StandardScalerParamsWhether to center the data with mean before scaling. It will build a dense output, so take care when applying to sparse input. Default: false- Specified by:
withMeanin interfaceStandardScalerParams- Returns:
- (undocumented)
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withStd
Description copied from interface:StandardScalerParamsWhether to scale the data to unit standard deviation. Default: true- Specified by:
withStdin interfaceStandardScalerParams- Returns:
- (undocumented)
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outputCol
Description copied from interface:HasOutputColParam for output column name.- Specified by:
outputColin interfaceHasOutputCol- Returns:
- (undocumented)
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inputCol
Description copied from interface:HasInputColParam for input column name.- Specified by:
inputColin interfaceHasInputCol- Returns:
- (undocumented)
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uid
Description copied from interface:IdentifiableAn immutable unique ID for the object and its derivatives.- Specified by:
uidin interfaceIdentifiable- Returns:
- (undocumented)
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setInputCol
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setOutputCol
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setWithMean
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setWithStd
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fit
Description copied from class:EstimatorFits a model to the input data.- Specified by:
fitin classEstimator<StandardScalerModel>- Parameters:
dataset- (undocumented)- Returns:
- (undocumented)
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transformSchema
Description 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 classPipelineStage- Parameters:
schema- (undocumented)- Returns:
- (undocumented)
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copy
Description 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 interfaceParams- Specified by:
copyin classEstimator<StandardScalerModel>- Parameters:
extra- (undocumented)- Returns:
- (undocumented)
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