We are excited to announce PredictionIO version 0.9 is now available. We want to thank you for all your feedback and contributions so far!

These are the major improvements in 0.9:

Machine Learning Analytics

Using the Event Server, our open source machine learning analytics layer for unifying events from multiple platforms, we now support batch import of events using the pio import command.

Furthermore, you can now export data to Apache Parquet format with the pio export command. We already support several popular analytics tools, including IPython Notebook, Tableau and Zeppelin.

Zeppelin PredictionIO Analytics

Engine Templates allow you to quickly build production-ready predictive **engines or customize templates for your unique prediction requirements.

We recently announced our first 5 templates for E-commerce use cases:

  • E-Commerce Recommendation
  • Complementary Purchase
  • Product Ranking
  • Similar Product
  • Lead Scoring

Engine Templates follow PredictionIO’s DASE architectural pattern (Data, Algorithm, Serving and Evaluation) allowing you to re-use and customize individual components. This separation of concern shortens the development cycle and enable rapid deployment.

Using the pio template list command you can now see the available Engine Templates.

Evaluation Metrics & Hyperparameter Tuning

We now support Evaluation Metrics and Hyperparameter Tuning, the “E” in DASE, for example, for Classification our Engine Template supports Precision as a simple metric to compare the predicted result returned from the Engine and the actual result which we obtained from the test data. The pio eval command kick starts the evaluation and we support implementing and contributing you own Evaluation Metrics!

Engine Debugging & Troubleshooting

To further support development of predictive engines we now offer methods for debugging, including partial engine training and sanity checking, see our Troubleshooting Engine Development docs.

Community Contributions

Other Community Contribution highlights include GraphX Parallel SimRank Algorithm by Joey Zhou and Swift SDK for iOS / OS X by Minh Tu Le.

You can see the Release Notes, Upgrade Instructions and install PredictionIO 0.9: https://docs.prediction.io/install/

You can find Quick Start tutorials for all our Engine Templates (e.g., Complementary Purchase) via: https://templates.prediction.io/

We are delighted by the support from the community and we look forward to hearing your feedback on this latest release!

By Simon Chan