Machine Learning Index Stage
The Fusion machine learning indexing stage uses a trained machine learning model to analyze a field or fields of a PipelineDocument and stores the results of analysis in a new field of either the PipelineDocument or 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:
Invokes a machine learning model to make a prediction on a document during indexing.
skip - boolean
Set to true to skip this stage.
Default: false
label - string
A unique label for this stage.
<= 255 characters
condition - string
Define a conditional script that must result in true or false. This can be used to determine if the stage should process or not.
modelId - stringrequired
The ID of the ML model stored in the Fusion blob store. If you trained a model using a Fusion Job, by default the model ID will be the same as the job name.
>= 1 characters
docFeatureFieldName - stringrequired
Name of fields to feed into the model. Can be a single field name, or multiple field names are supported in this format: field1:weight,field2:weight,field3:weight
>= 1 characters
Default: body_t
predictionFieldName - stringrequired
Name of the field to store the prediction (model output) in the document.
defaultValue - string
Value to provide if a prediction cannot be made
failOnError - boolean
Flag to indicate if this stage should throw an exception if an error occurs while generating a prediction for a document.
Default: false
storeInContext - boolean
Flag to indicate that the prediction should be set as a context property instead of setting a field on the document.
Default: false
includeRawPredictions - boolean
Flag to indicate that raw predictions and scores, in addition to the best prediction, should be set on the document.
Default: false