Cosine Distance. Defined as 1 - cosine similarity.
We strongly suggest using DOT_PRODUCT_DISTANCE + UNIT_L2_NORM instead
of COSINE distance. Our algorithms have been more optimized for
DOT_PRODUCT distance which, when combined with UNIT_L2_NORM, is
mathematically equivalent to COSINE distance and results in the same
ranking.
DotProductDistance
Dot Product Distance. Defined as a negative of the dot product.
[[["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 webpage provides reference documentation for the `FeatureView.Types.IndexConfig.Types.DistanceMeasureType` enum within the Google Cloud AI Platform v1 API."],["The latest version of the API documented here is 3.22.0, with older versions going back to 1.0.0 also being accessible through the provided links."],["The `DistanceMeasureType` enum defines the distance metrics used in nearest neighbor searches, including `CosineDistance`, `DotProductDistance`, `SquaredL2Distance`, and `Unspecified`."],["The documentation offers guidance on using `DOT_PRODUCT_DISTANCE` and `UNIT_L2_NORM` over `COSINE` for optimized algorithms, despite their mathematical equivalence."],["The namespace for the information provided in this document is `Google.Cloud.AIPlatform.V1`, found within the `Google.Cloud.AIPlatform.V1.dll` assembly."]]],[]]
