Package | Description |
---|---|
net.librec.data | |
net.librec.data.convertor | |
net.librec.math.structure | |
net.librec.recommender |
Modifier and Type | Method and Description |
---|---|
SparseTensor |
DataConvertor.getSparseTensor()
Returns a
SparseTensor object which stores rate data. |
Modifier and Type | Field and Description |
---|---|
protected SparseTensor |
AbstractDataConvertor.sparseTensor
store rate data as a sparse tensor
|
Modifier and Type | Method and Description |
---|---|
SparseTensor |
AbstractDataConvertor.getSparseTensor()
Return the rate tensor.
|
Modifier and Type | Method and Description |
---|---|
SparseTensor |
SparseTensor.clone()
make a deep clone
|
SparseTensor |
SparseTensor.modeProduct(DenseMatrix mat,
int dim)
n-mode product of a tensor A (I1 x I2 x ...
|
SparseTensor |
SparseTensor.modeProduct(DenseVector vec,
int dim)
n-mode product of a tensor A (I1 x I2 x ...
|
Modifier and Type | Method and Description |
---|---|
double |
SparseTensor.innerProduct(SparseTensor st) |
boolean |
SparseTensor.isDimMatch(SparseTensor st)
Return whether two sparse tensors have the same dimensions
|
Modifier and Type | Field and Description |
---|---|
protected SparseTensor |
TensorRecommender.testTensor
testTensor
|
protected SparseTensor |
FactorizationMachineRecommender.testTensor
testTensor
|
protected SparseTensor |
TensorRecommender.trainTensor
train Tensor
|
protected SparseTensor |
FactorizationMachineRecommender.trainTensor
train Tensor
|
protected SparseTensor |
TensorRecommender.validTensor
validTensor
|
protected SparseTensor |
FactorizationMachineRecommender.validTensor
validTensor
|
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