:: DeveloperApi :: Engine developers should not use this directly.
:: DeveloperApi :: Engine developers should not use this directly. This is called by evaluation workflow to perform batch prediction.
Spark context
Model
Batch of queries
Batch of predicted results
:: DeveloperApi :: Engine developers should not use this directly.
:: DeveloperApi :: Engine developers should not use this directly. Called by serving to perform a single prediction.
Model
Query
Predicted result
:: DeveloperApi :: Engine developers should not use this directly.
:: DeveloperApi :: Engine developers should not use this directly. This is called by workflow to train a model.
Spark context
Prepared data
Trained model
:: DeveloperApi :: Serializer for Java query classes using Gson
:: DeveloperApi :: Serializer for Java query classes using Gson
:: DeveloperApi :: Engine developers should not use this directly.
:: DeveloperApi :: Engine developers should not use this directly. Prepare a model for persistence in the downstream consumer. PredictionIO supports 3 types of model persistence: automatic persistence, manual persistence, and re-training on deployment. This method provides a way for downstream modules to determine which mode the model should be persisted.
Spark context
Model ID
Algorithm parameters that trained this model
Model
The model itself for automatic persistence, an instance of org.apache.predictionio.workflow.PersistentModelManifest for manual persistence, or Unit for re-training on deployment
:: DeveloperApi :: Obtains the type signature of query for this algorithm
:: DeveloperApi :: Obtains the type signature of query for this algorithm
Type signature of query
:: DeveloperApi :: Serializer for Scala query classes using org.apache.predictionio.controller.Utils.json4sDefaultFormats
:: DeveloperApi :: Serializer for Scala query classes using org.apache.predictionio.controller.Utils.json4sDefaultFormats
:: DeveloperApi :: Base class of all algorithm controllers
Prepared data class
Model class
Query class
Predicted result class