Reference documentation and code samples for the Vertex AI v1beta1 API enum StudySpec.Types.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.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-03-25 UTC."],[[["This document provides reference information for the `StudySpec.Types.MeasurementSelectionType` enum within the Vertex AI v1beta1 API, specifically in the Google.Cloud.AIPlatform.V1Beta1 namespace."],["The `MeasurementSelectionType` enum determines how the service selects a final measurement from intermediate measurements, considering factors such as whether improvements are expected to be monotonic or if measurements are noisy."],["The enum offers three fields: `BestMeasurement` for selecting the best reported measurement, `LastMeasurement` for selecting the most recent reported measurement, and `Unspecified`, which defaults to `LastMeasurement`."],["Choosing between `BestMeasurement` and `LastMeasurement` depends on whether the measurements are expected to improve monotonically or if they are significantly noisy, as `BestMeasurement` may be over-optimistic in the latter case."]]],[]]
