Collaborative Filter Recommender
Using the model trained by the Collaborative Filter Trainer, outputs recommendations for those users or products.
Configuration
Parameter | Description |
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Notes | Any notes or helpful information about this operator's parameter settings. When you enter content in the Notes field, a yellow asterisk is displayed on the operator. |
Generate Recommendations for |
Select a column in your data set that represents either users or product IDs.
To see a list of products that a user might like, choose User (the default). To see a list of users who might like a product, choose Product. |
This Column Represents | Indicates what the Generate Recommendations for column represents - Users (the default) or Products. |
Number to Recommend | Specify the number of recommendations to generate.
Range: 1-100. Default value: 5. |
Output Directory | The location to store the output files. |
Output Name | The name to contain the results. |
Overwrite Output | Specifies whether to delete existing data at that path. |
Storage Format | Select the format in which to store the results. The storage format is determined by your type of operator.
Typical formats are Avro, CSV, TSV, or Parquet. |
Compression | Select the type of compression for the output.
Available Avro compression options. |
Advanced Spark Settings Automatic Optimization |
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Output
- Visual Output
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This output shows each user ID in the users column selected, then lists five products they might enjoy and their predicted ratings.
- Data Output
- This data can be further manipulated by other operators in your workflow. It is passed on as a tabular HDFS data set. You can find the storage location of the recommendation table by referring to the Summary section of the results pane, as shown in the following example.
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