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An engine can virtually call any algorithm in the Algorithm class. Apache PredictionIO (incubating) currently offers native support to Spark MLlib machine learning library. It is being used by some of the engine templates in the template galler y.

More library support will be added soon.

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You can use more than one algorithm to build multiple models in an engine. The predicted results can be combined in the Serving class.

Here are some How-to examples:

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Every engine template comes with default algorithm(s). To switch to another algorithm, you simply need to modify the Algorithm class.

Here are some How-to examples:

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Apache PredictionIO (incubating) is designed as a machine learning server that integrates with your applications on production environments.

A web or mobile app normal ly:

  1. Send event data to Apache PredictionIO (incubating)'s Event Server for model training
  2. Send dynamic queries to deployed engine(s) to retrieve predicted results

Apache PredictionIO (incubating) Single Engine Overview

Sending Event Data

Apache PredictionIO (incubating)'s Event Server receives event data from your application. The data can be used by engines as training data to build preditive models.

Event Server listens to port 7070 by default. You can change the port with the --port arg when you launch the Event Server.

For further information, please read:

Sendi ng Query

After you deploy an engine as a web service, it will wait for queries from your application and return predicted results in JSON format. An engine listens to port 8000 by default. If you want to deploy multiple engines, you can specific a different port for each of them.

For further information, please read:

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