org.apache.spark.ml.recommendation
Whether the overall frequency of items should be used instead of the frequency of items per user Default: false
Whether the overall frequency of items should be used instead of the frequency of items per user Default: false
Whether the items of a user should be filtered from the recommendations for the user Default: false
Whether the items of a user should be filtered from the recommendations for the user Default: false
The name of the item id column of integers from 0 to number of items in training dataset Default: "itemid"
The name of the item id column of integers from 0 to number of items in training dataset Default: "itemid"
Returns top numItems items recommended for each user id in the input data set
Returns top numItems items recommended for each user id in the input data set
The dataset containing a column of user ids. The column name must match userCol
The maximum number of recommendations for each user
A dataframe of (userCol: Int, recommendations), where recommendations are stored as an array of (score: Float, itemCol: Int) rows. Or if exploded a dataframe of (userCol: Int, score: Float, itemCol: Int) rows.
The name of the user id column of integers Default: "userid"
The name of the user id column of integers Default: "userid"
Model fitted by PopRank.