| --- |
| title: Glossary |
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| |
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| |
| **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. |
