Class Imputer
- All Implemented Interfaces:
- Serializable,- org.apache.spark.internal.Logging,- ImputerParams,- Params,- HasInputCol,- HasInputCols,- HasOutputCol,- HasOutputCols,- HasRelativeError,- DefaultParamsWritable,- Identifiable,- MLWritable
Note when an input column is integer, the imputed value is casted (truncated) to an integer type. For example, if the input column is IntegerType (1, 2, 4, null), the output will be IntegerType (1, 2, 4, 2) after mean imputation.
Note that the mean/median/mode value is computed after filtering out missing values. All Null values in the input columns are treated as missing, and so are also imputed. For computing median, DataFrameStatFunctions.approxQuantile is used with a relative error of 0.001.
- 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.Fits a model to the input data.inputCol()Param for input column name.final StringArrayParamParam for input column names.static Imputerfinal DoubleParamThe placeholder for the missing values.Param for output column name.final StringArrayParamParam for output column names.static MLReader<T>read()final DoubleParamParam for the relative target precision for the approximate quantile algorithm.setInputCol(String value) setInputCols(String[] value) setMissingValue(double value) setOutputCol(String value) setOutputCols(String[] value) setRelativeError(double value) setStrategy(String value) Imputation strategy.strategy()The imputation strategy.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.PipelineStageparamsMethods inherited from class java.lang.Objectequals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitMethods inherited from interface org.apache.spark.ml.util.DefaultParamsWritablewriteMethods 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.ml.param.shared.HasRelativeErrorgetRelativeErrorMethods inherited from interface org.apache.spark.ml.util.IdentifiabletoStringMethods inherited from interface org.apache.spark.ml.feature.ImputerParamsgetInOutCols, getMissingValue, getStrategy, validateAndTransformSchemaMethods inherited from interface org.apache.spark.internal.LogginginitializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, org$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, 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- 
Imputer
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Imputerpublic Imputer()
 
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Method Details- 
load
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read
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strategyDescription copied from interface:ImputerParamsThe imputation strategy. Currently only "mean" and "median" are supported. If "mean", then replace missing values using the mean value of the feature. If "median", then replace missing values using the approximate median value of the feature. If "mode", then replace missing using the most frequent value of the feature. Default: mean- Specified by:
- strategyin interface- ImputerParams
- Returns:
- (undocumented)
 
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missingValueDescription copied from interface:ImputerParamsThe placeholder for the missing values. All occurrences of missingValue will be imputed. Note that null values are always treated as missing. Default: Double.NaN- Specified by:
- missingValuein interface- ImputerParams
- Returns:
- (undocumented)
 
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relativeErrorDescription copied from interface:HasRelativeErrorParam for the relative target precision for the approximate quantile algorithm. Must be in the range [0, 1].- Specified by:
- relativeErrorin interface- HasRelativeError
- 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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setInputCol
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setOutputCol
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setInputCols
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setOutputCols
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setStrategyImputation strategy. Available options are ["mean", "median", "mode"].- Parameters:
- value- (undocumented)
- Returns:
- (undocumented)
 
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setMissingValue
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setRelativeError
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fitDescription copied from class:EstimatorFits a model to the input data.- Specified by:
- fitin class- Estimator<ImputerModel>
- 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- Estimator<ImputerModel>
- Parameters:
- extra- (undocumented)
- Returns:
- (undocumented)
 
 
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