DatasetDataSource allows you to perform explainability analysis on a random
sample of data from a specified environment/dataset. This is useful for
understanding general model behavior, analyzing feature importance patterns
across multiple instances, or getting representative explanations.
This data source type is ideal for exploratory analysis, understanding overall
model behavior, or when you want to analyze explanations across a representative
sample rather than specific instances.
Examples
Creating a dataset data source for production sampling:
Creating a dataset data source for validation analysis:
Creating a dataset data source with default sampling:
Attributes
Data source type discriminator; fixed as ENVIRONMENT.
Environment to sample from; accepts an EnvType value or its string name. Number of rows to sample for the analysis (optional).
ID of the environment (dataset) to sample from; serialized as dataset_id.
