Using H2O Driverless AI
May 2020: Version 1.8.6
Contents
Section | Title | Page |
---|---|---|
1 | Overview | 6 |
1.1 | Citation | 6 |
1.2 | Have Questions? | 6 |
2 | Why Driverless AI? | 7 |
3 | Key Features | 8 |
4 | Supported Algorithms | 10 |
5 | Installing and Upgrading Driverless AI | 12 |
6 | Launching Driverless AI | 13 |
6.1 | Messages | 14 |
7 | The Datasets Page | 14 |
7.1 | Adding Datasets | 15 |
7.2 | Dataset Details | 17 |
7.2.1 | Dataset Details Page | 17 |
7.2.2 | Dataset Rows Page | 19 |
7.2.3 | Modify by Recipe | 19 |
7.2.4 | Downloading Datasets | 20 |
7.3 | Splitting Datasets | 21 |
7.4 | Visualizing Datasets | 22 |
7.4.1 | The Visualization Page | 22 |
8 | Running an Experiment | 26 |
8.1 | Before You Begin | 26 |
8.2 | New Experiment | 26 |
8.3 | Completed Experiment | 30 |
8.4 | Model Scores | 31 |
8.4.1 | Experiment Summary | 33 |
8.5 | Viewing Experiments | 36 |
8.5.1 | Checkpointing, Rerunning, and Retraining | 36 |
8.5.2 | Deleting Experiments | 39 |
9 | Diagnosing a Model | 3 |
10 | Project Workspace | 41 |
10.1 | Linking Datasets | 42 |
10.1.1 | Selecting Datasets | 42 |
10.2 | Linking Experiments | 43 |
10.2.1 | New Experiments | 43 |
10.2.2 | Checkpointing Experiments | 44 |
10.3 | The Experiments Leaderboard | 44 |
10.3.1 | Leaderboard Scoring | 45 |
10.3.2 | Comparing Experiments | 46 |
10.4 | Unlinking Data on a Projects Page | 48 |
10.5 | Deleting Projects | 48 |
11 | Interpreting a Model | 48 |
11.1 | Interpret this Model button – Regular Experiments | 49 |
11.2 | Interpret this Model button – Time-Series Experiments | 50 |
11.2.1 | Multi-Group Time Series MLI | 50 |
11.2.2 | Single Time Series MLI | 52 |
11.3 | Model Interpretation – Driverless AI Models | 54 |
11.4 | Model Interpretation – External Models | 57 |
11.5 | Understanding the Model Interpretation Page | 59 |
11.5.1 | Summary Page | 61 |
11.5.2 | DAI Model Dropdown | 61 |
11.5.3 | Random Forest Dropdown | 77 |
11.5.4 | Dashboard Page | 80 |
11.6 | General Considerations | 81 |
11.6.1 | Machine Learning and Approximate Explanations | 81 |
11.6.2 | The Multiplicity of Good Models in Machine Learning | 82 |
11.6.3 | Expectations for Consistency Between Explanatory Techniques | 82 |
12 | Viewing Explanations | 83 |
13 | Score on Another Dataset | 86 |
14 | Transform Another Dataset | 86 |
15 | The Driverless AI Scoring Pipelines | 88 |
15.1 | Visualize the Scoring Pipeline | 88 |
15.2 | Which Pipeline Should I Use? | 90 |
15.3 | Driverless AI Standalone Python Scoring Pipeline | 91 |
15.3.1 | Python Scoring Pipeline Files | 91 |
15.3.2 | Quick Start – Recommended Method | 92 |
15.3.3 | Quick Start – Alternative Method | 93 |
15.3.4 | The Python Scoring Module | 96 |
15.3.5 | The Scoring Service | 96 |
15.3.6 | Python Scoring Pipeline FAQ | 99 |
15.3.7 | Troubleshooting Python Environment Issues | 99 |
15.4 | Driverless AI MLI Standalone Scoring Package | 100 |
15.4.1 | MLI Python Scoring Package Files | 101 |
15.4.2 | Quick Start – Recommended Method | 102 |
15.4.3 | Quick Start – Alternative Method | 102 |
15.4.4 | Prerequisites | 102 |
15.4.5 | MLI Python Scoring Module | 104 |
15.4.6 | K-LIME vs Shapley Reason Codes | 105 |
15.4.7 | MLI Scoring Service Overview | 105 |
15.5 | Driverless AI MOJO Scoring Pipeline | 108 |
15.5.1 | Prerequisites | 108 |
15.5.2 | MOJO Scoring Pipeline Files | 109 |
15.5.3 | Quickstart | 109 |
15.5.4 | Execute the MOJO from Java | 110 |
15.5.5 | MOJO Scoring Pipeline – C++ Solution | 112 |
15.5.5.1 | Downloading the Scoring Pipeline Runtimes | 112 |
16 | Deployment | 115 |
16.1 | Additional Resources | 116 |
16.2 | Deployments Overview Page | 116 |
16.3 | AWS Lambda Deployment | 116 |
16.3.1 | Driverless AI Prerequisites | 116 |
16.3.2 | AWS Access Permissions Prerequisites | 116 |
16.3.3 | Deploying the Lambda | 118 |
16.3.4 | Testing the Lambda Deployment | 119 |
16.3.5 | AWS Deployment Issues | 120 |
16.4 | REST Server Deployment | 121 |
16.4.1 | Prerequisites | 121 |
16.4.2 | Deploying on REST Server | 121 |
16.4.3 | Testing the REST Server Deployment | 123 |
16.4.4 | REST Server Deployment Issues | 124 |
17 | About Driverless AI Transformations | 125 |
17.1 | Numeric Transformers | 125 |
17.2 | Time Series Experiments Transformers | 126 |
17.3 | Categorical Transformers (String) | 127 |
17.4 | Text Transformers (String) | 128 |
17.5 | Time Transformers (Date, Time) | 129 |
18 | Logs | 129 |
18.1 | Sending Logs to H2O | 133 |
19 | References | 133 |
20 | Authors | 135 |
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