Package org.apache.spark.ml.regression

Interface AFTSurvivalRegressionParams

All Superinterfaces:
HasAggregationDepth, HasFeaturesCol, HasFitIntercept, HasLabelCol, HasMaxBlockSizeInMB, HasMaxIter, HasPredictionCol, HasTol, Identifiable, org.apache.spark.internal.Logging, Params, PredictorParams, Serializable, scala.Serializable
All Known Implementing Classes:
AFTSurvivalRegression, AFTSurvivalRegressionModel
public interface AFTSurvivalRegressionParams extends PredictorParams, HasMaxIter, HasTol, HasFitIntercept, HasAggregationDepth, HasMaxBlockSizeInMB, org.apache.spark.internal.Logging
Params for accelerated failure time (AFT) regression.

  • Method Details

    • censorCol

      Param<String> censorCol()
      Param for censor column name. The value of this column could be 0 or 1. If the value is 1, it means the event has occurred i.e. uncensored; otherwise censored.
      Returns:
      (undocumented)

    • getCensorCol

      String getCensorCol()

    • getQuantileProbabilities

      double[] getQuantileProbabilities()

    • getQuantilesCol

      String getQuantilesCol()

    • hasQuantilesCol

      boolean hasQuantilesCol()
      Checks whether the input has quantiles column name.

    • quantileProbabilities

      DoubleArrayParam quantileProbabilities()
      Param for quantile probabilities array. Values of the quantile probabilities array should be in the range (0, 1) and the array should be non-empty.
      Returns:
      (undocumented)

    • quantilesCol

      Param<String> quantilesCol()
      Param for quantiles column name. This column will output quantiles of corresponding quantileProbabilities if it is set.
      Returns:
      (undocumented)

    • validateAndTransformSchema

      StructType validateAndTransformSchema(StructType schema, boolean fitting)
      Validates and transforms the input schema with the provided param map.
      Parameters:
      schema - input schema
      fitting - whether this is in fitting or prediction
      Returns:
      output schema