All Implemented Interfaces:

Serializable, org.apache.spark.internal.Logging, TargetEncoderBase, Params, HasHandleInvalid, HasInputCol, HasInputCols, HasLabelCol, HasOutputCol, HasOutputCols, Identifiable, MLWritable

param: stats Array of statistics for each input feature. Array( Map( category, (counter, stat) ) )

See Also:

• Serialized Form

• Nested Class Summary

  Nested Classes

  Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging

  org.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 how to handle invalid data during transform().

  inputCol()

  Param for input column name.

  inputCols()

  Param for input column names.

  labelCol()

  Param for label column name.

  outputCol()

  Param for output column name.

  Param for output column names.

  read()

  setSmoothing(double value)

  smoothing()

  toString()

  Transforms the input dataset.

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

  uid()

  An immutable unique ID for the object and its derivatives.

  write()

  Returns an MLWriter instance for this ML instance.

  Methods inherited from interface org.apache.spark.internal.Logging

  initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logBasedOnLevel, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, MDC, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, withLogContext

  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, estimateMatadataSize, 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

  • handleInvalid

    Param for how to handle invalid data during transform(). Options are 'keep' (invalid data presented as an extra categorical feature) or 'error' (throw an error). Note that this Param is only used during transform; during fitting, invalid data will result in an error. Default: "error"

    Specified by:

    handleInvalid in interface HasHandleInvalid

    Specified by:

    handleInvalid in interface TargetEncoderBase

    Returns:

    (undocumented)

  • targetType

    Specified by:

    targetType in interface TargetEncoderBase

  • smoothing

    Specified by:

    smoothing in interface TargetEncoderBase

  • 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

    Description copied from interface: HasInputCol

    Param for input column name.

    Specified by:

    inputCol in interface HasInputCol

    Returns:

    (undocumented)

  • labelCol

    Description copied from interface: HasLabelCol

    Param for label column name.

    Specified by:

    labelCol in interface HasLabelCol

    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

  • setHandleInvalid

  • setSmoothing

  • 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)

  • transform

    Transforms the input dataset.

    Specified by:

    transform in class Transformer

    Parameters:

    dataset - (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<TargetEncoderModel>

    Parameters:

    extra - (undocumented)

    Returns:

    (undocumented)

  • write

    Description copied from interface: MLWritable

    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