Description Usage Arguments Value Note See Also Examples
sInitial
is supposed to initialise an object of class "sInit"
given a topology and input data. As a matter of fact, it initialises
the codebook matrix (in input high-dimensional space). The return
object inherits the topology information (i.e., a "sTopol" object from
sTopology
), along with initialised codebook matrix and method
used.
1 2 |
data |
a data frame or matrix of input data |
sTopol |
an object of class "sTopol" (see |
init |
an initialisation method. It can be one of "uniform", "sample" and "linear" initialisation methods |
seed |
an integer specifying the seed |
an object of class "sInit", a list with following components:
nHex
: the total number of hexagons/rectanges in the grid
xdim
: x-dimension of the grid
ydim
: y-dimension of the grid
r
: the hypothetical radius of the grid
lattice
: the grid lattice
shape
: the grid shape
coord
: a matrix of nHex x 2, with each row corresponding
to the coordinates of a hexagon/rectangle in the 2D map grid
init
: an initialisation method
codebook
: a codebook matrix of nHex x ncol(data), with
each row corresponding to a prototype vector in input high-dimensional
space
call
: the call that produced this result
The initialisation methods include:
"uniform": the codebook matrix is uniformly initialised via randomly taking any values within the interval [min, max] of each column of input data
"sample": the codebook matrix is initialised via randomly sampling/selecting input data
"linear": the codebook matrix is linearly initialised along the first two greatest eigenvectors of input data
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | # 1) generate an iid normal random matrix of 100x10
data <- matrix( rnorm(100*10,mean=0,sd=1), nrow=100, ncol=10)
# 2) from this input matrix, determine nHex=5*sqrt(nrow(data))=50,
# but it returns nHex=61, via "sHexGrid(nHex=50)", to make sure a supra-hexagonal grid
sTopol <- sTopology(data=data, lattice="hexa", shape="suprahex")
# 3) initialise the codebook matrix using different mehtods
# 3a) using "uniform" method
sI_uniform <- sInitial(data=data, sTopol=sTopol, init="uniform")
# 3b) using "sample" method
# sI_sample <- sInitial(data=data, sTopol=sTopol, init="sample")
# 3c) using "linear" method
# sI_linear <- sInitial(data=data, sTopol=sTopol, init="linear")
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