Class Imputer
- All Implemented Interfaces:
Serializable
,org.apache.spark.internal.Logging
,ImputerParams
,Params
,HasInputCol
,HasInputCols
,HasOutputCol
,HasOutputCols
,HasRelativeError
,DefaultParamsWritable
,Identifiable
,MLWritable
,scala.Serializable
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 Summary
Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging
org.apache.spark.internal.Logging.SparkShellLoggingFilter
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Constructor Summary
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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.final StringArrayParam
Param for input column names.static Imputer
final DoubleParam
The placeholder for the missing values.Param for output column name.final StringArrayParam
Param for output column names.static MLReader<T>
read()
final DoubleParam
Param 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.PipelineStage
params
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
Methods inherited from interface org.apache.spark.ml.util.DefaultParamsWritable
write
Methods inherited from interface org.apache.spark.ml.param.shared.HasInputCol
getInputCol
Methods inherited from interface org.apache.spark.ml.param.shared.HasInputCols
getInputCols
Methods inherited from interface org.apache.spark.ml.param.shared.HasOutputCol
getOutputCol
Methods inherited from interface org.apache.spark.ml.param.shared.HasOutputCols
getOutputCols
Methods inherited from interface org.apache.spark.ml.param.shared.HasRelativeError
getRelativeError
Methods inherited from interface org.apache.spark.ml.util.Identifiable
toString
Methods inherited from interface org.apache.spark.ml.feature.ImputerParams
getInOutCols, getMissingValue, getStrategy, validateAndTransformSchema
Methods inherited from interface org.apache.spark.internal.Logging
initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq
Methods inherited from interface org.apache.spark.ml.util.MLWritable
save
Methods inherited from interface org.apache.spark.ml.param.Params
clear, 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
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Imputer
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Imputer
public Imputer()
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Method Details
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load
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read
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strategy
Description copied from interface:ImputerParams
The 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:
strategy
in interfaceImputerParams
- Returns:
- (undocumented)
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missingValue
Description copied from interface:ImputerParams
The 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:
missingValue
in interfaceImputerParams
- Returns:
- (undocumented)
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relativeError
Description copied from interface:HasRelativeError
Param for the relative target precision for the approximate quantile algorithm. Must be in the range [0, 1].- Specified by:
relativeError
in interfaceHasRelativeError
- Returns:
- (undocumented)
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outputCols
Description copied from interface:HasOutputCols
Param for output column names.- Specified by:
outputCols
in interfaceHasOutputCols
- Returns:
- (undocumented)
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outputCol
Description copied from interface:HasOutputCol
Param for output column name.- Specified by:
outputCol
in interfaceHasOutputCol
- Returns:
- (undocumented)
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inputCols
Description copied from interface:HasInputCols
Param for input column names.- Specified by:
inputCols
in interfaceHasInputCols
- Returns:
- (undocumented)
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inputCol
Description copied from interface:HasInputCol
Param for input column name.- Specified by:
inputCol
in interfaceHasInputCol
- Returns:
- (undocumented)
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uid
Description copied from interface:Identifiable
An immutable unique ID for the object and its derivatives.- Specified by:
uid
in interfaceIdentifiable
- 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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setStrategy
Imputation 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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fit
Description copied from class:Estimator
Fits a model to the input data.- Specified by:
fit
in classEstimator<ImputerModel>
- Parameters:
dataset
- (undocumented)- Returns:
- (undocumented)
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transformSchema
Description copied from class:PipelineStage
Check transform validity and derive the output schema from the input schema.We check validity for interactions between parameters during
transformSchema
and 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:
transformSchema
in classPipelineStage
- Parameters:
schema
- (undocumented)- Returns:
- (undocumented)
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copy
Description copied from interface:Params
Creates 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:
copy
in interfaceParams
- Specified by:
copy
in classEstimator<ImputerModel>
- Parameters:
extra
- (undocumented)- Returns:
- (undocumented)
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