runSOM {CytoTree} | R Documentation |
Build a self-organizing map
runSOM( object, xdim = 6, ydim = 6, rlen = 8, mst = 1, alpha = c(0.05, 0.01), radius = 1, init = FALSE, distf = 2, codes = NULL, importance = NULL, method = "euclidean", verbose = FALSE, ... )
object |
an CYT object |
xdim |
Width of the grid. |
ydim |
Hight of the grid. |
rlen |
Number of times to loop over the training data for each MST |
mst |
Number of times to build an MST |
alpha |
Start and end learning rate |
radius |
Start and end radius |
init |
Initialize cluster centers in a non-random way |
distf |
Distance function (1=manhattan, 2=euclidean, 3=chebyshev, 4=cosine) |
codes |
Cluster centers to start with |
importance |
array with numeric values. Parameters will be scaled according to importance |
method |
the distance measure to be used. This must be one of "euclidean",
"maximum", "manhattan", "canberra", "binary" or "minkowski".
Any unambiguous substring can be given. See |
verbose |
logical. Whether to print calculation progress. |
... |
Parameters passing to |
an CYT object with som.id in CYT object
This code is strongly based on the SOM
function.
Which is developed by Sofie Van Gassen, Britt Callebaut and Yvan Saeys (2018).
cyt.file <- system.file("extdata/cyt.rds", package = "CytoTree") cyt <- readRDS(file = cyt.file) cyt <- runSOM(cyt, xdim = 10, ydim = 10, verbose = TRUE)