Scales the feasible space logarithmically to (0, 1). The entire
feasible space must be strictly positive.
UnitReverseLogScale
Scales the feasible space "reverse" logarithmically to (0, 1). The
result is that values close to the top of the feasible space are spread
out more than points near the bottom. The entire feasible space must be
strictly positive.
[[["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 2025-03-21 UTC."],[[["This document provides reference information for the `StudySpec.Types.ParameterSpec.Types.ScaleType` enum within the Vertex AI v1beta1 API, specifically for .NET development."],["The `ScaleType` enum defines different methods for scaling parameters, including linear, logarithmic, and reverse logarithmic scaling, alongside an option for no scaling."],["The available scale types are `UnitLinearScale`, `UnitLogScale`, `UnitReverseLogScale`, and `Unspecified`, each with distinct scaling behaviors and constraints."],["This documentation outlines how each scaling type transforms the feasible space of a parameter, with `UnitLogScale` and `UnitReverseLogScale` requiring strictly positive feasible spaces."],["The code examples and descriptions are found in the `Google.Cloud.AIPlatform.V1Beta1` namespace, within the `Google.Cloud.AIPlatform.V1Beta1.dll` assembly."]]],[]]
