| numero.evaluate {Numero} | R Documentation |
Self-organizing map statistics
Description
Evaluate regional variation of data values on a self-organizing map
Usage
numero.evaluate(model, data, ranked = TRUE, n = 1000)
Arguments
model |
A list object that contains a self-organizing map and a data layout. |
data |
A matrix or a data frame. |
ranked |
If true, a rank transform is applied to avoid problems from skewed distributions or outliers. |
n |
Maximum number of permutations per data column. |
Details
The input argument model can be the output from
numero.create() or from numero.quality().
Value
A list with named elements: som contains the self-organizing map,
layout contains the district assignments for data points,
planes contains smoothed district averages from
nroAggregate(), the element ranges contains the
reference ranges to be used in nroColorize(),
the element statistics contains the output from
nroPermute(), the element palette is the name of
the colormap and the element data contains the data points
that were used for calculating the statistics.
Examples
# Import data.
fname <- system.file("extdata", "finndiane.txt", package = "Numero")
dataset <- read.delim(file = fname)
# Set identities and manage missing data.
dataset <- numero.clean(dataset, identity = "INDEX")
# Prepare training variables.
trvars <- c("CHOL", "HDL2C", "TG", "CREAT", "uALB")
trdata <- numero.prepare(data = dataset, variables = trvars)
# Create a self-organizing map.
sm <- numero.create(data = trdata)
qc <- numero.quality(model = sm)
# Evaluate map statistics.
results <- numero.evaluate(model = qc, data = dataset)
print(results$statistics[,c("TRAINING", "Z", "P.z", "P.freq")])