The Machine Learning query pipeline stage uses a trained machine learning model to analyze a field or fields of a Request object and stores the results of analysis in a new field added to either the Request or the Context object.
In order to use the Machine Learning Stage, you must train a machine learning model. There are two different ways to train a model:
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Use a Fusion job that trains a model, like Logistic Regression or Random Forest.
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Train a model using Spark’s MLlib API outside of Fusion, and upload this model into Fusion’s blob store. Complete details are available in Machine Learning Models in Fusion.
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Tip
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When specifying field names, multiple field names are supported, in this format: field1:weight,field2:weight,field3:weight
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