View source: R/numero.evaluate.R
numero.evaluate | R Documentation |
Evaluate regional variation of data values on a self-organizing map
numero.evaluate(model, data, ranked = TRUE, n = 1000)
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. |
The input argument model
can be the output from
numero.create()
or from numero.quality()
.
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.
# 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")])
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