Data Preparator - Part of Engine. It reads data from source and transforms it to the desired format.

Data Source - Part of Engine. It preprocesses the data and forward it to the algorithm for model training.

Engine - An Engine represents a type of prediction, e.g. product recommendation. It is comprised of four components: [D] Data Source and Data Preparator, [A] Algorithm, [S] Serving, [E] Evaluation Metrics.

EngineClient - Part of PredictionSDK. It sends queries to a deployed engine instance through the Engine API and retrives prediction results.

Event API - Please see Event Server.

Event Server - Event Server is designed to collect data into PredictionIO in an event-based style. Once the Event Server is launched, your application can send data to it through its Event API with HTTP requests or with the EventClient of PredictionIO's SDKs.

EventClient - Please see Event Server.

Live Evaluation - Evaluation of prediction results in a production environment. Prediction results are shown to real users. Users do not rate the results explicitly but the system observes user behaviors such as click through rate.

Offline Evaluation - The prediction results are compared with pre-compiled offline datasets. Typically, offline evaluations are meant to identify the most promising approaches.

Test Data - Also commonly referred as Test Set. A set of data used to assess the strength and utility of a predictive relationship.

Training Data - Also commonly referred as Training Set. A set of data used to discover potentially predictive relationships. In PredictionIO Engine, training data is processed through the Data layer and passed onto algorithm.