Completed Experiment¶
After an experiment status changes from RUNNING to COMPLETE, the UI provides you with several options:
- Deploy: Refer to Deploying the MOJO Pipeline. (By default, this option is disabled until the MOJO Scoring Pipeline has been built. In addition, this option is not available for PPC64LE environments.)
- Interpret this Model: Refer to Interpreting a Model. (Not supported for NLP experiments. Please contact H2O support for assistance with interpreting NLP experiments.)
- Diagnose Model on New Dataset: Refer to Diagnosing a Model.
- Score on Another Dataset: Refer to Score on Another Dataset.
- Transform Another Dataset: Refer to Transform Another Dataset. (Not available for Time Series experiments.)
- Download Predictions dropdown:
- Training (Holdout) Predictions: In csv format, available if a validation set was NOT provided.
- Validation Set Predictions: In csv format, available if a validation set was provided.
- Test Set Predictions: In csv format, available if a test dataset is used.
- Download Python Scoring Pipeline: A standalone Python scoring pipeline for H2O Driverless AI. Refer to Driverless AI Standalone Python Scoring Pipeline.
- Build MOJO Scoring Pipeline: A standalone Model Object, Optimized scoring pipeline. Refer to Driverless AI MOJO Scoring Pipeline - Java runtime. (Not available for TensorFlow, RuleFit, or FTRL models.)
- Download Experiment Summary: A zip file containing the following files. Refer to the Experiment Summary section for more information.
- A summary of the experiment
- The experiment features along with their relative importance
- Ensemble information
- An experiment preview
- Word version of an auto-generated report for the experiment
- A target transformations tuning leaderboard
- A tuning leaderboard
- Download Logs
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