tbmClustering: Perform tensor clustering via tensor block model (TBM)

In tensorsparse: Multiway Clustering via Tensor Block Models

Description

Perform tensor clustering via tensor block model (TBM) method.

Usage

tbmClustering(
  x,
  k,
  r,
  l,
  lambda = 0,
  max.iter = 1000,
  threshold = 1e-10,
  sim.times = 1,
  trace = FALSE,
  Cs.init = NULL,
  Ds.init = NULL,
  Es.init = NULL,
  method = "L0"
)

Arguments

x	an order-3 data tensor
k	an positive integer, the numbers of clusters at mode 1
r	an positive integer, the numbers of clusters at mode 2
l	an positive integer, the numbers of clusters at mode 3
lambda	a numeric value, regularization coefficient
max.iter	a positive integer, the maximum numbers of iteration
threshold	a positive small numeric value for convergence threshold
sim.times	the number of simulation replicates when performing clustering
trace	logic value, print result per each iteration if TRUE
Cs.init	vector or NULL, initial cluster label assignment at mode 1
Ds.init	vector or NULL, initial cluster label assignment at mode 2
Es.init	vector or NULL, initial cluster label assignment at mode 3
method	two options: "L0", "L1". "L0" indicates L0 penalty, and "L1" indicates Lasso penalty

Value

a list

judgeX estimated underlying signal tensor

Cs clustering result at mode 1

Ds clustering result at mode 2

Es clustering result at mode 3

mus estimated block means

Author(s)

Yuchen Zeng [e-mail]

References

M. Wang and Y. Zeng, "Multiway clustering via tensoe block models". Advances in Neural Information Processing System 32 (NeurIPS), 715-725, 2019.

Examples

x = getOrder3Tensor(20,20,20,2,2,2)$x
tbmClustering(x,2,2,2)

tensorsparse documentation built on Jan. 8, 2021, 5:40 p.m.