Modifier and Type | Method and Description |
---|---|
DenseMatrix |
SVD.getS()
Return the diagonal matrix of singular values
|
DenseMatrix |
SVD.getU()
Return the left singular vectors
|
DenseMatrix |
SVD.getV()
Return the right singular vectors
|
static DenseMatrix |
Randoms.wishart(DenseMatrix scale,
double df)
Randomly sample a matrix from Wishart Distribution with the given parameters.
|
Modifier and Type | Method and Description |
---|---|
static DenseMatrix |
Randoms.wishart(DenseMatrix scale,
double df)
Randomly sample a matrix from Wishart Distribution with the given parameters.
|
Constructor and Description |
---|
SVD(DenseMatrix mat)
Construct the singular value decomposition Structure to access U, S and V.
|
Modifier and Type | Method and Description |
---|---|
DenseMatrix |
DenseMatrix.add(DenseMatrix mat)
Do
A + B matrix operation |
DenseMatrix |
DenseMatrix.add(double val)
Do
A + c matrix operation, where c is a constant. |
DenseMatrix |
DenseMatrix.add(SparseMatrix mat)
Do
A + B matrix operation |
DenseMatrix |
DenseMatrix.addEqual(DenseMatrix mat)
Do
A + B matrix operation |
DenseMatrix |
DenseMatrix.addEqual(double val)
Do
A + c matrix operation, where c is a constant. |
DenseMatrix |
DenseMatrix.addEqual(SparseMatrix mat)
Do
A + B matrix operation |
DenseMatrix |
DenseMatrix.cholesky() |
DenseMatrix |
DenseMatrix.clone()
Make a deep copy of current matrix
|
DenseMatrix |
DenseMatrix.cov() |
static DenseMatrix |
DenseMatrix.eye(int dim)
Construct an identity matrix
|
DenseMatrix |
DenseMatrix.getSubMatrix(int rowStart,
int rowEnd,
int colStart,
int colEnd)
Return a sub matrix of this matrix.
|
static DenseMatrix |
DenseMatrix.hadamardProduct(DenseMatrix M,
DenseMatrix N)
Return Hadamard product of two matrices.
|
DenseMatrix |
DenseMatrix.inv()
NOTE: this implementation (adopted from PREA package) is slightly faster than
inverse , especially when
numRows is large. |
DenseMatrix |
DenseMatrix.inverse()
Deprecated.
use
inv instead which is slightly faster |
static DenseMatrix |
DenseMatrix.khatriRaoProduct(DenseMatrix M,
DenseMatrix N)
Return Khatri-Rao product of two matrices.
|
static DenseMatrix |
DenseMatrix.kroneckerProduct(DenseMatrix M,
DenseMatrix N)
Return Kronecker product of two arbitrary matrices
|
DenseMatrix |
DenseMatrix.minus(DenseMatrix mat)
Do
A - B matrix operation |
DenseMatrix |
DenseMatrix.minus(double val)
Do
A - c matrix operation, where c is a constant. |
DenseMatrix |
DenseMatrix.minus(SparseMatrix mat)
Do
A - B matrix operation |
DenseMatrix |
DenseMatrix.minusEqual(DenseMatrix mat)
Do
A - B matrix operation |
DenseMatrix |
DenseMatrix.minusEqual(double val)
Do
A - c matrix operation, where c is a constant. |
DenseMatrix |
DenseMatrix.minusEqual(SparseMatrix mat)
Do
A - B matrix operation |
DenseMatrix |
DenseMatrix.mult(DenseMatrix mat)
Matrix multiplication with a dense matrix
|
DenseMatrix |
DenseMatrix.mult(SparseMatrix mat)
Matrix multiplication with a sparse matrix
|
static DenseMatrix |
DenseMatrix.mult(SparseMatrix sm,
DenseMatrix dm)
Matrix multiplication of a sparse matrix by a dense matrix
|
DenseMatrix |
DenseVector.outer(DenseVector vec)
Do vector operation:
a * b^t |
DenseMatrix |
DenseMatrix.pinv() |
DenseMatrix |
DenseMatrix.scale(double val)
Return a new matrix by scaling the current matrix.
|
DenseMatrix |
DenseMatrix.scaleEqual(double val)
Return this matrix by scaling the current matrix.
|
DenseMatrix |
DenseMatrix.transMult() |
DenseMatrix |
DenseMatrix.transpose() |
Modifier and Type | Method and Description |
---|---|
DenseMatrix |
DenseMatrix.add(DenseMatrix mat)
Do
A + B matrix operation |
DenseMatrix |
DenseMatrix.addEqual(DenseMatrix mat)
Do
A + B matrix operation |
static double |
DenseMatrix.colMult(DenseMatrix m,
int mcol,
DenseMatrix n,
int ncol)
Inner product of two column vectors
|
static DenseMatrix |
DenseMatrix.hadamardProduct(DenseMatrix M,
DenseMatrix N)
Return Hadamard product of two matrices.
|
static DenseMatrix |
DenseMatrix.khatriRaoProduct(DenseMatrix M,
DenseMatrix N)
Return Khatri-Rao product of two matrices.
|
static DenseMatrix |
DenseMatrix.kroneckerProduct(DenseMatrix M,
DenseMatrix N)
Return Kronecker product of two arbitrary matrices
|
DenseMatrix |
DenseMatrix.minus(DenseMatrix mat)
Do
A - B matrix operation |
DenseMatrix |
DenseMatrix.minusEqual(DenseMatrix mat)
Do
A - B matrix operation |
SparseTensor |
SparseTensor.modeProduct(DenseMatrix mat,
int dim)
n-mode product of a tensor A (I1 x I2 x ...
|
DenseMatrix |
DenseMatrix.mult(DenseMatrix mat)
Matrix multiplication with a dense matrix
|
static DenseMatrix |
DenseMatrix.mult(SparseMatrix sm,
DenseMatrix dm)
Matrix multiplication of a sparse matrix by a dense matrix
|
static double |
DenseMatrix.product(DenseMatrix m,
int mrow,
DenseMatrix n,
int ncol)
Dot product of row x col between two matrices.
|
static double |
DenseMatrix.rowMult(DenseMatrix m,
int mrow,
DenseMatrix n,
int nrow)
Inner product of two row vectors
|
Constructor and Description |
---|
DenseMatrix(DenseMatrix mat)
Construct a dense matrix by copying data from a given matrix
|
Modifier and Type | Field and Description |
---|---|
protected DenseMatrix |
MatrixFactorizationRecommender.itemFactors
item latent factors
|
protected DenseMatrix |
FactorizationMachineRecommender.Q
parameter matrix
|
protected DenseMatrix |
MatrixFactorizationRecommender.userFactors
user latent factors
|
protected DenseMatrix |
FactorizationMachineRecommender.V
parameter matrix
|
Modifier and Type | Field and Description |
---|---|
protected DenseMatrix |
LDARecommender.topicItemNumbers
entry[k, i]: number of tokens assigned to topic k, given item i.
|
protected DenseMatrix |
PLSARecommender.topicItemProbs
Conditional Probability: P(i|z)
|
protected DenseMatrix |
LDARecommender.topicItemProbs
posterior probabilities of parameters
|
protected DenseMatrix |
AspectModelRecommender.topicItemProbs
Conditional distribution: P(i|z)
|
protected DenseMatrix |
PLSARecommender.topicItemProbsSum
Conditional Probability: P(i|z)
|
protected DenseMatrix |
LDARecommender.topicItemProbsSum
cumulative statistics of theta, phi
|
protected DenseMatrix |
AspectModelRecommender.topicItemProbsSum
Conditional distribution: P(i|z)
|
protected DenseMatrix |
AspectModelRecommender.topicUserProbs
Conditional distribution: P(u|z)
|
protected DenseMatrix |
AspectModelRecommender.topicUserProbsSum
Conditional distribution: P(u|z)
|
protected DenseMatrix |
LDARecommender.userTopicNumbers
entry[u, k]: number of tokens assigned to topic k, given user u.
|
protected DenseMatrix |
ItemBigramRecommender.userTopicNumbers
entry[u, k]: number of tokens assigned to topic k, given user u.
|
protected DenseMatrix |
PLSARecommender.userTopicProbs
Conditional Probability: P(z|u)
|
protected DenseMatrix |
LDARecommender.userTopicProbs
posterior probabilities of parameters
|
protected DenseMatrix |
ItemBigramRecommender.userTopicProbs
posterior probabilities of parameters
|
protected DenseMatrix |
PLSARecommender.userTopicProbsSum
Conditional Probability: P(z|u)
|
protected DenseMatrix |
LDARecommender.userTopicProbsSum
cumulative statistics of theta, phi
|
protected DenseMatrix |
ItemBigramRecommender.userTopicProbsSum
cumulative statistics of theta, phi
|
Modifier and Type | Method and Description |
---|---|
double |
ListRankMFRecommender.getLoss(DenseMatrix userFactors,
DenseMatrix itemFactors) |
Modifier and Type | Field and Description |
---|---|
protected DenseMatrix |
SVDPlusPlusRecommender.impItemFactors
item implicit feedback factors, "imp" string means implicit
|
protected DenseMatrix |
ASVDPlusPlusRecommender.impItemFactors |
protected DenseMatrix |
BPoissMFRecommender.GammaDenseMatrix.logValue |
protected DenseMatrix |
BPoissMFRecommender.GammaDenseMatrixGR.logValue |
protected DenseMatrix |
ASVDPlusPlusRecommender.neiItemFactors |
protected DenseMatrix |
BPoissMFRecommender.GammaDenseMatrix.rate |
protected DenseMatrix |
BPoissMFRecommender.GammaDenseMatrix.shape |
protected DenseMatrix |
BPoissMFRecommender.GammaDenseMatrixGR.shape |
protected DenseMatrix |
GPLSARecommender.topicItemMu |
protected DenseMatrix |
AspectModelRecommender.topicItemProbs |
protected DenseMatrix |
AspectModelRecommender.topicItemProbsSum |
protected DenseMatrix |
GPLSARecommender.topicItemSigma |
protected DenseMatrix |
AspectModelRecommender.topicUserProbs |
protected DenseMatrix |
AspectModelRecommender.topicUserProbsSum |
protected DenseMatrix |
GPLSARecommender.userTopicProbs |
protected DenseMatrix |
BPoissMFRecommender.GammaDenseMatrix.value |
protected DenseMatrix |
BPoissMFRecommender.GammaDenseMatrixGR.value |
DenseMatrix |
BPMFRecommender.HyperParameters.variance |
Modifier and Type | Method and Description |
---|---|
DenseMatrix |
LLORMAUpdater.getLocalItemFactors()
Getter method for item profile of this local model.
|
DenseMatrix |
LLORMAUpdater.getLocalUserFactors()
Getter method for user profile of this local model.
|
Modifier and Type | Method and Description |
---|---|
protected DenseVector |
BPoissMFRecommender.getPhi(DenseMatrix Theta,
int indexTheta,
DenseMatrix Beta,
int indexBeta,
int number) |
protected BPMFRecommender.HyperParameters |
BPMFRecommender.samplingHyperParameters(BPMFRecommender.HyperParameters hyperParameters,
DenseMatrix factors,
DenseVector normalMu0,
double normalBeta0,
DenseMatrix WishartScale0,
double WishartNu0) |
protected DenseVector |
BPMFRecommender.updateParameters(DenseMatrix factors,
SparseVector ratings,
BPMFRecommender.HyperParameters hyperParameters) |
Modifier and Type | Field and Description |
---|---|
protected DenseMatrix |
EFMRecommender.featureMatrix |
protected DenseMatrix |
HFTRecommender.itemFactors
item latent factors
|
protected DenseMatrix |
EFMRecommender.itemFactors
item latent factors
|
protected DenseMatrix |
EFMRecommender.itemFeatureMatrix |
protected DenseMatrix |
EFMRecommender.itemFeatureQuality |
protected DenseMatrix |
EFMRecommender.itemHiddenMatrix |
protected DenseMatrix |
HFTRecommender.topicToWord |
protected DenseMatrix |
HFTRecommender.userFactors
user latent factors
|
protected DenseMatrix |
EFMRecommender.userFactors
user latent factors
|
protected DenseMatrix |
EFMRecommender.userFeatureAttention |
protected DenseMatrix |
EFMRecommender.userFeatureMatrix |
protected DenseMatrix |
EFMRecommender.userHiddenMatrix |
Modifier and Type | Field and Description |
---|---|
protected DenseMatrix |
TimeSVDRecommender.P
factorized user-factor matrix
|
protected DenseMatrix |
TimeSVDRecommender.Q
factorized item-factor matrix
|
protected DenseMatrix |
TrustMFRecommender.trusteeItemFactors
trustee model
|
protected DenseMatrix |
TrustMFRecommender.trusteeUserTrusteeFactors
trustee model
|
protected DenseMatrix |
TrustMFRecommender.trusteeUserTrusterFactors
trustee model
|
protected DenseMatrix |
TrustMFRecommender.trusterItemFactors
truster model
|
protected DenseMatrix |
TrustMFRecommender.trusterUserTrusteeFactors
truster model
|
protected DenseMatrix |
TrustMFRecommender.trusterUserTrusterFactors
truster model
|
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