Packages

final class ChiSqSelector extends Selector[ChiSqSelectorModel]

Chi-Squared feature selection, which selects categorical features to use for predicting a categorical label. The selector supports different selection methods: numTopFeatures, percentile, fpr, fdr, fwe.

  • numTopFeatures chooses a fixed number of top features according to a chi-squared test.
  • percentile is similar but chooses a fraction of all features instead of a fixed number.
  • fpr chooses all features whose p-value are below a threshold, thus controlling the false positive rate of selection.
  • fdr uses the [Benjamini-Hochberg procedure] (https://en.wikipedia.org/wiki/False_discovery_rate#Benjamini.E2.80.93Hochberg_procedure) to choose all features whose false discovery rate is below a threshold.
  • fwe chooses all features whose p-values are below a threshold. The threshold is scaled by 1/numFeatures, thus controlling the family-wise error rate of selection. By default, the selection method is numTopFeatures, with the default number of top features set to 50.
Annotations
@deprecated @Since( "1.6.0" )
Deprecated

(Since version 3.1.1) use UnivariateFeatureSelector instead

Source
ChiSqSelector.scala
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Inherited
  1. ChiSqSelector
  2. Selector
  3. DefaultParamsWritable
  4. MLWritable
  5. SelectorParams
  6. HasOutputCol
  7. HasLabelCol
  8. HasFeaturesCol
  9. Estimator
  10. PipelineStage
  11. Logging
  12. Params
  13. Serializable
  14. Serializable
  15. Identifiable
  16. AnyRef
  17. Any
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Parameters

A list of (hyper-)parameter keys this algorithm can take. Users can set and get the parameter values through setters and getters, respectively.

  1. final val fdr: DoubleParam

    The upper bound of the expected false discovery rate.

    The upper bound of the expected false discovery rate. Only applicable when selectorType = "fdr". Default value is 0.05.

    Definition Classes
    SelectorParams
    Annotations
    @Since( "3.1.0" )
  2. final val featuresCol: Param[String]

    Param for features column name.

    Param for features column name.

    Definition Classes
    HasFeaturesCol
  3. final val fpr: DoubleParam

    The highest p-value for features to be kept.

    The highest p-value for features to be kept. Only applicable when selectorType = "fpr". Default value is 0.05.

    Definition Classes
    SelectorParams
    Annotations
    @Since( "3.1.0" )
  4. final val fwe: DoubleParam

    The upper bound of the expected family-wise error rate.

    The upper bound of the expected family-wise error rate. Only applicable when selectorType = "fwe". Default value is 0.05.

    Definition Classes
    SelectorParams
    Annotations
    @Since( "3.1.0" )
  5. final val labelCol: Param[String]

    Param for label column name.

    Param for label column name.

    Definition Classes
    HasLabelCol
  6. final val numTopFeatures: IntParam

    Number of features that selector will select, ordered by ascending p-value.

    Number of features that selector will select, ordered by ascending p-value. If the number of features is less than numTopFeatures, then this will select all features. Only applicable when selectorType = "numTopFeatures". The default value of numTopFeatures is 50.

    Definition Classes
    SelectorParams
    Annotations
    @Since( "3.1.0" )
  7. final val outputCol: Param[String]

    Param for output column name.

    Param for output column name.

    Definition Classes
    HasOutputCol
  8. final val percentile: DoubleParam

    Percentile of features that selector will select, ordered by ascending p-value.

    Percentile of features that selector will select, ordered by ascending p-value. Only applicable when selectorType = "percentile". Default value is 0.1.

    Definition Classes
    SelectorParams
    Annotations
    @Since( "3.1.0" )
  9. final val selectorType: Param[String]

    The selector type.

    The selector type. Supported options: "numTopFeatures" (default), "percentile", "fpr", "fdr", "fwe"

    Definition Classes
    SelectorParams
    Annotations
    @Since( "3.1.0" )

Members

  1. final def clear(param: Param[_]): ChiSqSelector.this.type

    Clears the user-supplied value for the input param.

    Clears the user-supplied value for the input param.

    Definition Classes
    Params
  2. def copy(extra: ParamMap): ChiSqSelector

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

    Definition Classes
    ChiSqSelector → Selector → EstimatorPipelineStageParams
    Annotations
    @Since( "1.6.0" )
  3. def explainParam(param: Param[_]): String

    Explains a param.

    Explains a param.

    param

    input param, must belong to this instance.

    returns

    a string that contains the input param name, doc, and optionally its default value and the user-supplied value

    Definition Classes
    Params
  4. def explainParams(): String

    Explains all params of this instance.

    Explains all params of this instance. See explainParam().

    Definition Classes
    Params
  5. final def extractParamMap(): ParamMap

    extractParamMap with no extra values.

    extractParamMap with no extra values.

    Definition Classes
    Params
  6. final def extractParamMap(extra: ParamMap): ParamMap

    Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values less than user-supplied values less than extra.

    Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values less than user-supplied values less than extra.

    Definition Classes
    Params
  7. def fit(dataset: Dataset[_]): ChiSqSelectorModel

    Fits a model to the input data.

    Fits a model to the input data.

    Definition Classes
    ChiSqSelector → Selector → Estimator
    Annotations
    @Since( "1.6.0" )
  8. def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[ChiSqSelectorModel]

    Fits multiple models to the input data with multiple sets of parameters.

    Fits multiple models to the input data with multiple sets of parameters. The default implementation uses a for loop on each parameter map. Subclasses could override this to optimize multi-model training.

    dataset

    input dataset

    paramMaps

    An array of parameter maps. These values override any specified in this Estimator's embedded ParamMap.

    returns

    fitted models, matching the input parameter maps

    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  9. def fit(dataset: Dataset[_], paramMap: ParamMap): ChiSqSelectorModel

    Fits a single model to the input data with provided parameter map.

    Fits a single model to the input data with provided parameter map.

    dataset

    input dataset

    paramMap

    Parameter map. These values override any specified in this Estimator's embedded ParamMap.

    returns

    fitted model

    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  10. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): ChiSqSelectorModel

    Fits a single model to the input data with optional parameters.

    Fits a single model to the input data with optional parameters.

    dataset

    input dataset

    firstParamPair

    the first param pair, overrides embedded params

    otherParamPairs

    other param pairs. These values override any specified in this Estimator's embedded ParamMap.

    returns

    fitted model

    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  11. final def get[T](param: Param[T]): Option[T]

    Optionally returns the user-supplied value of a param.

    Optionally returns the user-supplied value of a param.

    Definition Classes
    Params
  12. final def getDefault[T](param: Param[T]): Option[T]

    Gets the default value of a parameter.

    Gets the default value of a parameter.

    Definition Classes
    Params
  13. final def getOrDefault[T](param: Param[T]): T

    Gets the value of a param in the embedded param map or its default value.

    Gets the value of a param in the embedded param map or its default value. Throws an exception if neither is set.

    Definition Classes
    Params
  14. def getParam(paramName: String): Param[Any]

    Gets a param by its name.

    Gets a param by its name.

    Definition Classes
    Params
  15. final def hasDefault[T](param: Param[T]): Boolean

    Tests whether the input param has a default value set.

    Tests whether the input param has a default value set.

    Definition Classes
    Params
  16. def hasParam(paramName: String): Boolean

    Tests whether this instance contains a param with a given name.

    Tests whether this instance contains a param with a given name.

    Definition Classes
    Params
  17. final def isDefined(param: Param[_]): Boolean

    Checks whether a param is explicitly set or has a default value.

    Checks whether a param is explicitly set or has a default value.

    Definition Classes
    Params
  18. final def isSet(param: Param[_]): Boolean

    Checks whether a param is explicitly set.

    Checks whether a param is explicitly set.

    Definition Classes
    Params
  19. lazy val params: Array[Param[_]]

    Returns all params sorted by their names.

    Returns all params sorted by their names. The default implementation uses Java reflection to list all public methods that have no arguments and return Param.

    Definition Classes
    Params
    Note

    Developer should not use this method in constructor because we cannot guarantee that this variable gets initialized before other params.

  20. def save(path: String): Unit

    Saves this ML instance to the input path, a shortcut of write.save(path).

    Saves this ML instance to the input path, a shortcut of write.save(path).

    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  21. final def set[T](param: Param[T], value: T): ChiSqSelector.this.type

    Sets a parameter in the embedded param map.

    Sets a parameter in the embedded param map.

    Definition Classes
    Params
  22. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  23. def transformSchema(schema: StructType): StructType

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

    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.

    Definition Classes
    ChiSqSelector → Selector → PipelineStage
    Annotations
    @Since( "1.6.0" )
  24. val uid: String

    An immutable unique ID for the object and its derivatives.

    An immutable unique ID for the object and its derivatives.

    Definition Classes
    ChiSqSelectorIdentifiable
    Annotations
    @Since( "1.6.0" )
  25. def write: MLWriter

    Returns an MLWriter instance for this ML instance.

    Returns an MLWriter instance for this ML instance.

    Definition Classes
    DefaultParamsWritableMLWritable

Parameter setters

  1. def setFdr(value: Double): ChiSqSelector.this.type

    Definition Classes
    ChiSqSelector → Selector
    Annotations
    @Since( "2.2.0" )
  2. def setFeaturesCol(value: String): ChiSqSelector.this.type

    Definition Classes
    ChiSqSelector → Selector
    Annotations
    @Since( "1.6.0" )
  3. def setFpr(value: Double): ChiSqSelector.this.type

    Definition Classes
    ChiSqSelector → Selector
    Annotations
    @Since( "2.1.0" )
  4. def setFwe(value: Double): ChiSqSelector.this.type

    Definition Classes
    ChiSqSelector → Selector
    Annotations
    @Since( "2.2.0" )
  5. def setLabelCol(value: String): ChiSqSelector.this.type

    Definition Classes
    ChiSqSelector → Selector
    Annotations
    @Since( "1.6.0" )
  6. def setNumTopFeatures(value: Int): ChiSqSelector.this.type

    Definition Classes
    ChiSqSelector → Selector
    Annotations
    @Since( "1.6.0" )
  7. def setOutputCol(value: String): ChiSqSelector.this.type

    Definition Classes
    ChiSqSelector → Selector
    Annotations
    @Since( "1.6.0" )
  8. def setPercentile(value: Double): ChiSqSelector.this.type

    Definition Classes
    ChiSqSelector → Selector
    Annotations
    @Since( "2.1.0" )
  9. def setSelectorType(value: String): ChiSqSelector.this.type

    Definition Classes
    ChiSqSelector → Selector
    Annotations
    @Since( "2.1.0" )

Parameter getters

  1. def getFdr: Double

    Definition Classes
    SelectorParams
  2. final def getFeaturesCol: String

    Definition Classes
    HasFeaturesCol
  3. def getFpr: Double

    Definition Classes
    SelectorParams
    Annotations
    @Since( "3.1.0" )
  4. def getFwe: Double

    Definition Classes
    SelectorParams
  5. final def getLabelCol: String

    Definition Classes
    HasLabelCol
  6. def getNumTopFeatures: Int

    Definition Classes
    SelectorParams
    Annotations
    @Since( "3.1.0" )
  7. final def getOutputCol: String

    Definition Classes
    HasOutputCol
  8. def getPercentile: Double

    Definition Classes
    SelectorParams
    Annotations
    @Since( "3.1.0" )
  9. def getSelectorType: String

    Definition Classes
    SelectorParams
    Annotations
    @Since( "3.1.0" )