Package | Description |
---|---|
org.nd4j.linalg.api.ops | |
org.nd4j.linalg.api.ops.impl.accum | |
org.nd4j.linalg.api.ops.impl.accum.distances |
Modifier and Type | Class and Description |
---|---|
class |
BaseLossFunction |
Modifier and Type | Class and Description |
---|---|
class |
ASum
Absolute sum the components
|
class |
Bias
Calculate a bias
|
class |
Dot
Dot product
|
class |
EqualsWithEps
Operation for fast INDArrays equality checks
|
class |
MatchCondition
Absolute sum the components
|
class |
Max
Calculate the max over a vector
|
class |
Mean
Calculate the mean of the vector
|
class |
Min
Calculate the min over a vector
|
class |
Norm1
Sum of absolute values
|
class |
Norm2
Sum of squared values (real)
Sum of squared complex modulus (complex)
|
class |
NormMax
The max absolute value
|
class |
Prod
Prod the components
|
class |
StandardDeviation
Standard deviation (sqrt of variance)
|
class |
Sum
Sum the components
|
class |
Variance
Variance with bias correction.
|
Modifier and Type | Class and Description |
---|---|
class |
CosineSimilarity
Cosine similarity
Note that you need to initialize
a scaling constant equal to the norm2 of the
vector
|
class |
EuclideanDistance
Euclidean distance
|
class |
ManhattanDistance
Manhattan distance
|
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