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.
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.