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Elastic

Inference for Supervised Learning

Priscilla Parodi
LinkedIn: https://www.linkedin.com/in/priscillaparodi/
Updated on ・2 min read

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Inference is a machine learning feature that enables you to use supervised machine learning processes – Regression or Classification – against incoming data.

Let's assume that you have an index with historical data and a classification model that is trained on this data and that you are receiving new data, with inference you can perform the classification against the new data with the same input fields that you've trained the model on, and get a prediction.

All you need to do is create an ingest pipeline with a configurable inference processor:

Kibana>Management>Stack Management>Ingest>Ingest Node Pipelines. Click on Create Pipeline.

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And add your inference processor:

Add a processor

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Processor = Inference>Add

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This post is part of a series that covers Artificial Intelligence with a focus on Elastic's (Creators of Elasticsearch, Kibana, Logstash and Beats) Machine Learning solution, aiming to introduce and exemplify the possibilities and options available, in addition to addressing the context and usability.

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