Package org.apache.spark.ml.recommendation

Interface ALSModelParams

All Superinterfaces:
HasBlockSize, HasPredictionCol, Identifiable, Params, Serializable, scala.Serializable
All Known Subinterfaces:
ALSParams
All Known Implementing Classes:
ALS, ALSModel
public interface ALSModelParams extends Params, HasPredictionCol, HasBlockSize
Common params for ALS and ALSModel.

  • Method Details

    • checkIntegers

      Column checkIntegers(Dataset<?> dataset, String colName)
      Attempts to safely cast a user/item id to an Int. Throws an exception if the value is out of integer range or contains a fractional part.
      Parameters:
      dataset - (undocumented)
      colName - (undocumented)
      Returns:
      (undocumented)

    • coldStartStrategy

      Param<String> coldStartStrategy()
      Param for strategy for dealing with unknown or new users/items at prediction time. This may be useful in cross-validation or production scenarios, for handling user/item ids the model has not seen in the training data. Supported values: - "nan": predicted value for unknown ids will be NaN. - "drop": rows in the input DataFrame containing unknown ids will be dropped from the output DataFrame containing predictions. Default: "nan".
      Returns:
      (undocumented)

    • getColdStartStrategy

      String getColdStartStrategy()

    • getItemCol

      String getItemCol()

    • getUserCol

      String getUserCol()

    • itemCol

      Param<String> itemCol()
      Param for the column name for item ids. Ids must be integers. Other numeric types are supported for this column, but will be cast to integers as long as they fall within the integer value range. Default: "item"
      Returns:
      (undocumented)

    • userCol

      Param<String> userCol()
      Param for the column name for user ids. Ids must be integers. Other numeric types are supported for this column, but will be cast to integers as long as they fall within the integer value range. Default: "user"
      Returns:
      (undocumented)