GenerateWmatricesandHmatrix | R Documentation |
\mathbf{W}
matrices in each modality and the shared \mathbf{H}
matrixCreate the \mathbf{W}^v
matrices and \mathbf{H}
matrix via non-negative double singular
value decomposition (NNDSVD) (Boutsidis and Gallopoulus 2008; Gaujoux and Seoighe 2010)
or randomization. For randomization, the algorithm runs for 10 rounds
for the desired number of random initializations and picks the \mathbf{W}^v
matrices and \mathbf{H}
matrix with
the lowest achieved loss.
GenerateWmatricesandHmatrix(
SickleJr,
d = 10,
random = FALSE,
numberReps = 100,
seed = 5,
minibatch = FALSE,
batchsize = -1,
random_W_updates = FALSE,
subsample = 1:dim(SickleJr@count.matrices[[1]])[2],
usesvd = FALSE
)
SickleJr |
An object of class SickleJr |
d |
Number of latent factors to use: defaults to 10 |
random |
Boolean indicating whether to use random initialization ( |
numberReps |
Number of random initializations to use: default is 5 |
seed |
Random seed for reproducibility of random initializations |
minibatch |
Indicates whether or not to use the mini-batch algorithm |
batchsize |
Size of batches for mini-batch NMF |
random_W_updates |
Indicates whether to only update each |
subsample |
A vector of values to use for subsampling; only appropriate when determining proper values for d. |
usesvd |
Indicates whether to use |
SickleJr An object of class SickleJr with the \mathbf{W}^v
matrices and \mathbf{H}
matrix added.
Boutsidis2008jrSiCKLSNMF
\insertRefNMFinRjrSiCKLSNMF
SimSickleJrSmall<-SetLambdasandRowReg(SimSickleJrSmall,
lambdaWlist=list(10,50),lambdaH=500,rowReg="None")
SimSickleJrSmall<-GenerateWmatricesandHmatrix(SimSickleJrSmall,d=5,usesvd=TRUE)
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