接口 UnivariateFeatureSelectorParams<T>

    • 字段详细资料

      • FEATURE_TYPE

        static final org.apache.flink.ml.param.Param<String> FEATURE_TYPE
        Supported options of the feature type.
        • categorical: the features are categorical data.
        • continuous: the features are continuous data.
      • LABEL_TYPE

        static final org.apache.flink.ml.param.Param<String> LABEL_TYPE
        Supported options of the label type.
        • categorical: the label is categorical data.
        • continuous: the label is continuous data.
      • SELECTION_MODE

        static final org.apache.flink.ml.param.Param<String> SELECTION_MODE
        Supported options of the feature selection mode.
        • numTopFeatures: chooses a fixed number of top features according to a hypothesis.
        • percentile: similar to numTopFeatures 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 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.
      • SELECTION_THRESHOLD

        static final org.apache.flink.ml.param.Param<Double> SELECTION_THRESHOLD
    • 方法详细资料

      • getFeatureType

        default String getFeatureType()
      • setFeatureType

        default T setFeatureType​(String value)
      • getLabelType

        default String getLabelType()
      • setLabelType

        default T setLabelType​(String value)
      • getSelectionMode

        default String getSelectionMode()
      • setSelectionMode

        default T setSelectionMode​(String value)
      • getSelectionThreshold

        default Double getSelectionThreshold()
      • setSelectionThreshold

        default T setSelectionThreshold​(double value)