VectorSearchAlgorithmMetric Class

Package:: com.azure.search.documents.indexes.models

Maven Artifact:: com.azure:azure-search-documents:11.8.1

java.lang.Object
- com.azure.core.util.ExpandableStringEnum<T>
- - com.azure.search.documents.indexes.models.VectorSearchAlgorithmMetric

public final class VectorSearchAlgorithmMetric
extends ExpandableStringEnum<VectorSearchAlgorithmMetric>

The similarity metric to use for vector comparisons. It is recommended to choose the same similarity metric as the embedding model was trained on.

Field Summary

Modifier and Type	Field and Description
static final VectorSearchAlgorithmMetric	COSINE Measures the angle between vectors to quantify their similarity, disregarding magnitude.
static final VectorSearchAlgorithmMetric	DOT_PRODUCT Calculates the sum of element-wise products to gauge alignment and magnitude similarity.
static final VectorSearchAlgorithmMetric	EUCLIDEAN Computes the straight-line distance between vectors in a multi-dimensional space.
static final VectorSearchAlgorithmMetric	HAMMING Only applicable to bit-packed binary data types.

Constructor Summary

Constructor	Description
VectorSearchAlgorithmMetric()	Deprecated Use the fromString(String name) factory method. Creates a new instance of VectorSearchAlgorithmMetric value.

Constructor

Description

VectorSearchAlgorithmMetric()

Deprecated

Use the fromString(String name) factory method.

Creates a new instance of VectorSearchAlgorithmMetric value.

Method Summary

Modifier and Type	Method and Description
static VectorSearchAlgorithmMetric	fromString(String name) Creates or finds a VectorSearchAlgorithmMetric from its string representation.
static Collection<VectorSearchAlgorithmMetric>	values() Gets known VectorSearchAlgorithmMetric values.

Methods inherited from ExpandableStringEnum

<T>fromString <T>values equals getValue hashCode toString

Methods inherited from java.lang.Object

clone finalize getClass notify notifyAll wait wait wait

Field Details

COSINE

public static final VectorSearchAlgorithmMetric COSINE

Measures the angle between vectors to quantify their similarity, disregarding magnitude. The smaller the angle, the closer the similarity.

DOT_PRODUCT

public static final VectorSearchAlgorithmMetric DOT_PRODUCT

Calculates the sum of element-wise products to gauge alignment and magnitude similarity. The larger and more positive, the closer the similarity.

EUCLIDEAN

public static final VectorSearchAlgorithmMetric EUCLIDEAN

Computes the straight-line distance between vectors in a multi-dimensional space. The smaller the distance, the closer the similarity.

HAMMING

public static final VectorSearchAlgorithmMetric HAMMING

Only applicable to bit-packed binary data types. Determines dissimilarity by counting differing positions in binary vectors. The fewer differences, the closer the similarity.

Constructor Details