@@ -70,23 +70,22 @@ Alternatively you could use any test classes from the `tools.descartes.librede.r
## Configuration
SARDE relies on EMF models to define run configurations for executions. The respective meta-model definition can be found [here](/tools.descartes.librede.rrde.model/model/lifecycle.ecore).
### LifeCycleConfiguration
One LifeCycleConfiguration object serves as a wrapper for one `OptimizationConfiguration` instance and one `RecommendationTrainingConfiguration` instance.
These specify the recommendation as well as the optimization process, if they are triggered.
If these references are not specified, they are ignored and not executed during the life-cycle of the tool.
The three Long parameters configurable in `LifeCycleConfiguration` define the time interval in which the events are cyclically triggered.
If they are set to `-1`, the configuration are just executed once and then never repeated.
However, a positive value for `recommendationLoopTime` defines the time in milliseconds between two repetitions of the defined `RecommendationTrainingConfiguration`, i.e., the re-training of the specified recommendation algorithm.
This might be useful, because the training set might change or augment in this interval.
Similarly the `optimizationLoopTime` defines the time interval in milliseconds between two executions of the `OptimizationConfiguration`.
The `selectionLoopTime` specifies the interval in milliseconds between to repetitions of the selection process executed by the trained algorithm.
If the extraction of the features by the `IFeatureExtractor` specified in the `RecommendationTrainingConfiguration` takes a considerably long time, it can be useful to omit the repetition of the selection for every estimation and to stick to the recommended estimator for a few iterations.
The following image visualizes the meta-model graphically:
