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

RobustScalerModel (Spark 4.0.0 JavaDoc)

All Implemented Interfaces:

Serializable, org.apache.spark.internal.Logging, RobustScalerParams, Params, HasInputCol, HasOutputCol, HasRelativeError, Identifiable, MLWritable

Model fitted by

.

param: range quantile range for each original column during fitting param: median median value for each original column during fitting

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

• Method Summary

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

  Param for input column name.

  Lower quantile to calculate quantile range, shared by all features Default: 0.25

  Param for output column name.

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

  Transforms the input dataset.

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

  An immutable unique ID for the object and its derivatives.

  Upper quantile to calculate quantile range, shared by all features Default: 0.75

  Whether to center the data with median before scaling.

  Whether to scale the data to quantile range.

  Returns an MLWriter instance for this ML instance.

  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

• Method Details
  • read
  • load
  • lower

    Lower quantile to calculate quantile range, shared by all features Default: 0.25

    Specified by:

    lower in interface RobustScalerParams

    Returns:

    (undocumented)

  • upper

    Upper quantile to calculate quantile range, shared by all features Default: 0.75

    Specified by:

    upper in interface RobustScalerParams

    Returns:

    (undocumented)

  • withCentering

    Whether to center the data with median before scaling. It will build a dense output, so take care when applying to sparse input. Default: false

    Specified by:

    withCentering in interface RobustScalerParams

    Returns:

    (undocumented)

  • withScaling

    Whether to scale the data to quantile range. Default: true

    Specified by:

    withScaling in interface RobustScalerParams

    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)

  • outputCol

    Param for output column name.

    Specified by:

    outputCol in interface HasOutputCol

    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)

  • range
  • median
  • setInputCol
  • setOutputCol
  • transform

    Transforms the input dataset.

    Specified by:

    transform in class Transformer

    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 Model<RobustScalerModel>

    Parameters:

    extra - (undocumented)

    Returns:

    (undocumented)

  • write

    Returns an MLWriter instance for this ML instance.

    Specified by:

    write in interface MLWritable

    Returns:

    (undocumented)

  • toString

    Specified by:

    toString in interface Identifiable

    Overrides:

    toString in class Object

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