Dataset validation flow
The flow of validating a dataset in H2O Model Validation can be summarized in the following sequential steps:
In the below sections, each step, in turn, is summarized.
Step 1: Select dataset
As the first step in the dataset validation flow, select a dataset. H2O Model Validation enables you to validate your datasets in an established Driverless AI (DAI) instance connection.
- To learn how to connect your DAI instance to H2O Model Validation, see Create a connection
Step 2: Run validation tests
As the second step in the dataset validation flow, run one or multiple validation tests for a dataset. To validate a dataset, H2O Model Validation offers two validation tests to analyze similar or dissimilar segments of two different datasets and to identify changes in the distribution of variables in your dataset. Note that specific validation tests are available to analyze a dataset. When selecting a validation test, each test offers several settings that you can adjust for total control over various factors of a validation test.
- Validation tests for a dataset:
Step 3: Review metrics
As the third and final step of the dataset validation flow, review validation test metrics. H2O Model Validation offers an array of metrics in graphs, charts, and heatmaps, enabling you to understand a validation test in detail.
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