Enum VectorDistanceType
- java.lang.Object
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- java.lang.Enum<VectorDistanceType>
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- io.objectbox.annotation.VectorDistanceType
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- All Implemented Interfaces:
java.io.Serializable
,java.lang.Comparable<VectorDistanceType>
public enum VectorDistanceType extends java.lang.Enum<VectorDistanceType>
The vector distance algorithm used by anHnswIndex
(vector search).
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Enum Constant Summary
Enum Constants Enum Constant Description COSINE
Cosine similarity compares two vectors irrespective of their magnitude (compares the angle of two vectors).DEFAULT
The default; currentlyEUCLIDEAN
.DOT_PRODUCT
For normalized vectors (vector length == 1.0), the dot product is equivalent to the cosine similarity.DOT_PRODUCT_NON_NORMALIZED
A custom dot product similarity measure that does not require the vectors to be normalized.EUCLIDEAN
Typically "Euclidean squared" internally.
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Method Summary
All Methods Static Methods Concrete Methods Modifier and Type Method Description static VectorDistanceType
valueOf(java.lang.String name)
Returns the enum constant of this type with the specified name.static VectorDistanceType[]
values()
Returns an array containing the constants of this enum type, in the order they are declared.
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Enum Constant Detail
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DEFAULT
public static final VectorDistanceType DEFAULT
The default; currentlyEUCLIDEAN
.
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EUCLIDEAN
public static final VectorDistanceType EUCLIDEAN
Typically "Euclidean squared" internally.
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COSINE
public static final VectorDistanceType COSINE
Cosine similarity compares two vectors irrespective of their magnitude (compares the angle of two vectors).Often used for document or semantic similarity.
Value range: 0.0 - 2.0 (0.0: same direction, 1.0: orthogonal, 2.0: opposite direction)
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DOT_PRODUCT
public static final VectorDistanceType DOT_PRODUCT
For normalized vectors (vector length == 1.0), the dot product is equivalent to the cosine similarity.Because of this, the dot product is often preferred as it performs better.
Value range (normalized vectors): 0.0 - 2.0 (0.0: same direction, 1.0: orthogonal, 2.0: opposite direction)
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DOT_PRODUCT_NON_NORMALIZED
public static final VectorDistanceType DOT_PRODUCT_NON_NORMALIZED
A custom dot product similarity measure that does not require the vectors to be normalized.Note: this is no replacement for cosine similarity (like DotProduct for normalized vectors is). The non-linear conversion provides a high precision over the entire float range (for the raw dot product). The higher the dot product, the lower the distance is (the nearer the vectors are). The more negative the dot product, the higher the distance is (the farther the vectors are).
Value range: 0.0 - 2.0 (nonlinear; 0.0: nearest, 1.0: orthogonal, 2.0: farthest)
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Method Detail
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values
public static VectorDistanceType[] values()
Returns an array containing the constants of this enum type, in the order they are declared. This method may be used to iterate over the constants as follows:for (VectorDistanceType c : VectorDistanceType.values()) System.out.println(c);
- Returns:
- an array containing the constants of this enum type, in the order they are declared
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valueOf
public static VectorDistanceType valueOf(java.lang.String name)
Returns the enum constant of this type with the specified name. The string must match exactly an identifier used to declare an enum constant in this type. (Extraneous whitespace characters are not permitted.)- Parameters:
name
- the name of the enum constant to be returned.- Returns:
- the enum constant with the specified name
- Throws:
java.lang.IllegalArgumentException
- if this enum type has no constant with the specified namejava.lang.NullPointerException
- if the argument is null
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