tModelEncoder
Performs featurization operations to transform data into the format expected by the model training components such as tLogisticRegressionModel or tKMeansModel.
tModelEncoder receives data from its preceding components, applies a wide range of feature processing algorithms to transform given columns of this data and sends the result to the model training component that follows to eventually train and create a predictive model.
In local mode, Apache Spark 2.4 and 3.0 are supported.
For more technologies supported by Talend, see Talend components.
Depending on the Talend product you are using, this component can be used in one, some or all of the following Job frameworks:
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Spark Batch: see tModelEncoder properties for Apache Spark Batch.
The component in this framework is available in all Talend Platform products with Big Data and in Talend Data Fabric.
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Spark Streaming: see tModelEncoder properties for Apache Spark Streaming.
This component is available in Talend Real Time Big Data Platform and Talend Data Fabric.
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