org.apache.spark.ml.recommendation

Interface ALSModelParams

All Superinterfaces:

HasBlockSize, HasPredictionCol, Identifiable, Params, java.io.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 Summary

Modifier and Type	Method and Description
Column	checkIntegers(Dataset<?> dataset, String colName) Attempts to safely cast a user/item id to an Int.
Param<String>	coldStartStrategy() Param for strategy for dealing with unknown or new users/items at prediction time.
String	getColdStartStrategy()
String	getItemCol()
String	getUserCol()
Param<String>	itemCol() Param for the column name for item ids.
Param<String>	userCol() Param for the column name for user ids.

Methods inherited from interface org.apache.spark.ml.param.shared.HasPredictionCol

getPredictionCol, predictionCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasBlockSize

blockSize, getBlockSize

Methods inherited from interface org.apache.spark.ml.param.Params

clear, copy, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

Methods inherited from interface org.apache.spark.ml.util.Identifiable

toString, uid

Method Detail

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)