Class RegressionMetrics (3.38.0)

RegressionMetrics(mapping=None, *, ignore_unknown_fields=False, **kwargs)

Evaluation metrics for regression and explicit feedback type matrix factorization models.

Attributes
Name	Description
`mean_absolute_error`	`google.protobuf.wrappers_pb2.DoubleValue` Mean absolute error.
`mean_squared_error`	`google.protobuf.wrappers_pb2.DoubleValue` Mean squared error.
`mean_squared_log_error`	`google.protobuf.wrappers_pb2.DoubleValue` Mean squared log error.
`median_absolute_error`	`google.protobuf.wrappers_pb2.DoubleValue` Median absolute error.
`r_squared`	`google.protobuf.wrappers_pb2.DoubleValue` R^2 score. This corresponds to r2_score in ML.EVALUATE.

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Last updated 2025-10-10 UTC.

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