Dataset validation flow

The following steps summarize the flow of validating a dataset in H2O Model Validation:

• Step 1: Establish a Connection and import a dataset
• Step 2: Run validation test(s)
• Step 3: Review test(s) metrics

For more information on each of the preceding steps, refer to the following sections.

Step 1: Establish a Connection and import a dataset

Establish a Connection that lets you import your datasets from one of the supported platforms. Once a Connection has been established, you can begin importing datasets.

• To learn how to establish a Connection, see Create a Connection.
• To learn how to import a dataset from an established Connection, see Import/upload a dataset.
• To learn about supported platforms, see Supported platforms.

Step 2: Run validation test(s)

Run one or multiple validation tests for the imported dataset. To validate a dataset, H2O Model Validation offers two validation tests to analyze similar or dissimilar segments of two different datasets and identify changes in the distribution of variables in your dataset. You can fine-tune the parameters of each test by using the available configuration settings.

• Validation tests for a dataset:
  • Adversarial similarity
    • To learn how to create an adversarial similarity test, see Create an adversarial similarity test.
  • Drift detection
    • To learn how to create a drift detection test, see Create a drift detection test.

Step 3: Review test(s) metrics

Review the validation test(s) metrics. For each validation test, H2O Model Validation offers a variety of metrics in graphs, charts, and heatmaps that let you assess the results of each test in detail.

• Metrics: Adversarial similarity
• Metrics: Drift detection

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