public sealed class IndexDatapoint.Types.SparseEmbedding : IMessage<IndexDatapoint.Types.SparseEmbedding>, IEquatable<IndexDatapoint.Types.SparseEmbedding>, IDeepCloneable<IndexDatapoint.Types.SparseEmbedding>, IBufferMessage, IMessage
Reference documentation and code samples for the Cloud AI Platform v1beta1 API class IndexDatapoint.Types.SparseEmbedding.
Feature embedding vector for sparse index. An array of numbers whose values
are located in the specified dimensions.
[[["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 2025-04-09 UTC."],[[["This documentation is for the `IndexDatapoint.Types.SparseEmbedding` class within the Cloud AI Platform v1beta1 API, specifically for version 1.0.0-beta02, with links to newer versions."],["`IndexDatapoint.Types.SparseEmbedding` represents a feature embedding vector designed for sparse indexes, where values are located in specified dimensions."],["The class implements multiple interfaces, including `IMessage`, `IEquatable`, `IDeepCloneable`, and `IBufferMessage`, providing functionalities like message handling, equality checks, deep cloning, and buffer operations."],["The class has two key properties: `Dimensions`, a list of long integers representing the indexes, and `Values`, a list of float values representing the embedding values, both required for the sparse vector."],["There are two constructors for creating a `SparseEmbedding`, one default and one that copies an existing `SparseEmbedding`."]]],[]]
