wccsom {wccsom} | R Documentation |
Self-organising maps for mapping high-dimensional spectra or patterns to 2D; instead of Euclidean distance, the weighted cross correlation (WCC) similarity measure is used. Modelled after the SOM function in package 'class'. wccsom takes 'continous' patterns, i.e. datapoints are equidistant.
wccsom(data, grid=somgrid(), rlen = 100, alpha = c(0.05, 0.01), radius = quantile(nhbrdist, 0.7), init, nhbrdist, trwidth = 20, toroidal = FALSE, FineTune = TRUE, keep.data = TRUE)
data |
Spectra or patterns to be mapped: a matrix, with each row representing a compound. |
grid |
A grid for the representatives: see 'somgrid'. |
rlen |
the number of times the complete data set will be presented to the network. |
alpha |
a vector of two numbers indicating the amount of
change. Default is to decline linearly from 0.05 to 0.01
over rlen updates. |
radius |
the initial radius of the neighbourhood to be used for
each update: the decrease is exponential over rlen updates in
such a way that after one-third of the updates only the winning unit
is updated. The default is to start with a
value that covers 2/3 of all units. |
init |
the initial representatives, represented as a matrix. If missing, chosen (without replacement) randomly from 'data'. |
nhbrdist |
optionally, the distance matrix for the units. |
trwidth |
width of the triangle function used in the WCC measure, given in the number of data points. |
toroidal |
if TRUE, then the edges of the map are joined. Note that in a toroidal hexagonal map, the number of rows must be even. |
FineTune |
apply kmeans for fine-tuning the codebook vectors. |
keep.data |
store training data and their mapping in the network. |
an object of class '"wccsom"' with components
grid |
the grid, an object of class '"somgrid"'. |
changes |
vector of mean average deviations from code vectors |
codes |
a matrix of code vectors. |
trwdth |
the triangle width used for the WCC measure |
acors |
autocorrelations of the code vectors. |
toroidal |
setting of parameter 'toroidal'. |
FineTune |
setting of parameter 'FineTune'. |
unit.classif |
mapping of training data: a vector of unit
numbers. Only if keep.data equals TRUE. |
wccs |
WCC values of all training data, compared to the best
matching codebook vector. Only if keep.data equals TRUE. |
data.acors |
WAC values for training data. Only if
keep.data equals TRUE. |
Ron Wehrens
R. Wehrens, W.J. Melssen, L.M.C. Buydens and R. de Gelder. Representing Structural Databases in a Self-Organising Map. Acta Cryst. B61, 548-557, 2005.
SOM
, plot.wccsom
,
wccxyf
, wcc
data(cepha) gr <- somgrid(3,3, "hexagonal") set.seed(7) x <- wccsom(cepha$patterns, grid=gr, trwidth=20, rlen=100)