Using Dynamic Learning Operators

Operators in StreamBase are components that perform a specific type of runtime action, such as filtering, merging, or querying, on the data streaming through them. You can separately configure each instance of an operator in StreamBase Studio using its Properties view.

The Dynamic Learning operators enable statistical and predictive analytics computed from streaming data, with results tables and statistics themselves delivered downstream as data streams. This will enable downstream consumers such as Spotfire to visualize in real-time results, such as correlations, feature importance (in some predictive analytics problem), or just standard Six-Sigma-type statistical summaries as they are commonly computed in manufacturing.

All the Dynamic Learning Operators have a dependency on the SMILE library to work.