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Showing content from http://spark.apache.org/docs/latest/api/java/org/apache/spark/ml/feature/Imputer.html below:

Imputer (Spark 4.0.0 JavaDoc)

All Implemented Interfaces:

Serializable, org.apache.spark.internal.Logging, ImputerParams, Params, HasInputCol, HasInputCols, HasOutputCol, HasOutputCols, HasRelativeError, DefaultParamsWritable, Identifiable, MLWritable

Imputation estimator for completing missing values, using the mean, median or mode of the columns in which the missing values are located. The input columns should be of numeric type. Currently Imputer does not support categorical features (SPARK-15041) and possibly creates incorrect values for a categorical feature.

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:

• Serialized Form

• Nested Class Summary
  Nested classes/interfaces inherited from interface org.apache.spark.internal.Loggingorg.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter

• Constructor Summary

  Constructors

• Method Summary

  Creates a copy of this instance with the same UID and some extra params.

  Fits a model to the input data.

  Param for input column name.

  Param for input column names.

  The placeholder for the missing values.

  Param for output column name.

  Param for output column names.

  Param for the relative target precision for the approximate quantile algorithm.

  Check transform validity and derive the output schema from the input schema.

  An immutable unique ID for the object and its derivatives.

  Methods 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, withLogContext
  Methods inherited from interface org.apache.spark.ml.util.MLWritablesave Methods 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

• Constructor Details
  • Imputer
  • Imputer

    public Imputer()

• Method Details
  • load
  • read
  • strategy

    Specified by:

    strategy in interface ImputerParams

    Returns:

    (undocumented)

  • missingValue

    Specified by:

    missingValue in interface ImputerParams

    Returns:

    (undocumented)

  • relativeError

    Param for the relative target precision for the approximate quantile algorithm. Must be in the range [0, 1].

    Specified by:

    relativeError in interface HasRelativeError

    Returns:

    (undocumented)

  • outputCols

    Param for output column names.

    Specified by:

    outputCols in interface HasOutputCols

    Returns:

    (undocumented)

  • outputCol

    Param for output column name.

    Specified by:

    outputCol in interface HasOutputCol

    Returns:

    (undocumented)

  • inputCols

    Param for input column names.

    Specified by:

    inputCols in interface HasInputCols

    Returns:

    (undocumented)

  • inputCol

    Param for input column name.

    Specified by:

    inputCol in interface HasInputCol

    Returns:

    (undocumented)

  • uid

    An immutable unique ID for the object and its derivatives.

    Specified by:

    uid in interface Identifiable

    Returns:

    (undocumented)

  • setInputCol
  • setOutputCol
  • setInputCols
  • setOutputCols
  • setStrategy

    Imputation strategy. Available options are ["mean", "median", "mode"].

    Parameters:

    value - (undocumented)

    Returns:

    (undocumented)

  • setMissingValue public Imputer setMissingValue(double value)
  • setRelativeError public Imputer setRelativeError(double value)
  • fit

    Fits a model to the input data.

    Specified by:

    fit in class Estimator<ImputerModel>

    Parameters:

    dataset - (undocumented)

    Returns:

    (undocumented)

  • transformSchema

    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 by Param.validate().

    Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.

    Specified by:

    transformSchema in class PipelineStage

    Parameters:

    schema - (undocumented)

    Returns:

    (undocumented)

  • 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. See defaultCopy().

    Specified by:

    copy in interface Params

    Specified by:

    copy in class Estimator<ImputerModel>

    Parameters:

    extra - (undocumented)

    Returns:

    (undocumented)

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