Vertex AI V1 API - Module Google::Cloud::AIPlatform::V1::StudySpec::MeasurementSelectionType (v1.40.0)

1.40.0 (latest) 1.39.0 1.38.0 1.37.0 1.36.0 1.35.0 1.34.0 1.33.0 1.32.0 1.31.0 1.30.1 1.29.0 1.28.0 1.27.0 1.26.0 1.25.0 1.24.0 1.23.1 1.22.0 1.21.0 1.20.0 1.19.0 1.18.0 1.17.0 1.16.0 1.15.0 1.14.0 1.13.0 1.12.0 1.11.0 1.10.0 1.9.0 1.8.0 1.7.0 1.6.0 1.5.0 1.4.0 1.3.0 1.2.0 1.1.0 1.0.0 0.64.0 0.63.0 0.62.0 0.61.0 0.60.0 0.59.0 0.58.0 0.57.0 0.56.0 0.55.0 0.54.0 0.53.0 0.52.0 0.51.0 0.50.0 0.49.0 0.48.0 0.47.0 0.46.0 0.45.0 0.44.0 0.43.0 0.42.0 0.41.0 0.40.0 0.39.0 0.38.0 0.37.0 0.36.0 0.35.0 0.34.0 0.33.0 0.32.0 0.31.0 0.30.0 0.29.0 0.28.0 0.27.0 0.26.0 0.25.0 0.24.0 0.23.0 0.22.0 0.21.0 0.20.0 0.19.0 0.18.0 0.17.0 0.16.0 0.15.0 0.14.0 0.13.0 0.12.0 0.11.0 0.10.0 0.9.1 0.8.0 0.7.0 0.6.0 0.5.0 0.4.0 0.3.0 0.2.0 0.1.0

Reference documentation and code samples for the Vertex AI V1 API module Google::Cloud::AIPlatform::V1::StudySpec::MeasurementSelectionType.

This indicates which measurement to use if/when the service automatically selects the final measurement from previously reported intermediate measurements. Choose this based on two considerations: A) Do you expect your measurements to monotonically improve? If so, choose LAST_MEASUREMENT. On the other hand, if you're in a situation where your system can "over-train" and you expect the performance to get better for a while but then start declining, choose BEST_MEASUREMENT. B) Are your measurements significantly noisy and/or irreproducible? If so, BEST_MEASUREMENT will tend to be over-optimistic, and it may be better to choose LAST_MEASUREMENT. If both or neither of (A) and (B) apply, it doesn't matter which selection type is chosen.

Constants

MEASUREMENT_SELECTION_TYPE_UNSPECIFIED

value: 0
Will be treated as LAST_MEASUREMENT.

LAST_MEASUREMENT

value: 1
Use the last measurement reported.

BEST_MEASUREMENT

value: 2
Use the best measurement reported.