som.nn.validate: Predict class labels for a validation dataset

In som.nn: Topological k-NN Classifier Based on Self-Organising Maps

Description

A model of type SOMnn is tested with a validation dataset. The dataset must include a column with correct class labels. The model is used to predict class labels. Confusion table, specificity, sensitivity and accuracy for each class are calculated.

Usage

som.nn.validate(model, x)

Arguments

model	model of type SOMnn.
x	data.fame with validation data. Samples are requested as rows. x must include the same columns as the data.frame with which the model have been trained originally. A column with correct class labels is needed. The column with class lables is selected by the slot class.idx of the model.

Details

Parameters stored in the model are applied for k-NN-like prediction. If necessary the parameters can be changed by som.nn.set before testing.

The funcion is only a wrapper and actually calls som.nn.continue with the test data and without training (i.e. len = 0).

Value

S4 object of type SOMnn with the unchanged model and the test statistics for the test data.

Examples

## get example data and add class labels:
data(iris)
species <- iris$Species

## train with default radius = diagonal / 2:
som <- som.nn.train(iris, class.col = "Species", kernel = "internal",
                    xdim = 15, ydim = 9, alpha = 0.2, len = 10000, 
                    norm = TRUE, toroidal = FALSE)


## continue training with different alpha and radius;
som <- som.nn.continue(som, iris, alpha = 0.02, len=1000, radius = 5)
som <- som.nn.continue(som, iris, alpha = 0.02, len=1000, radius = 2)

## predict some samples:
unk <- iris[,!(names(iris) %in% "Species")]

setosa <- unk[species=="setosa",]
setosa <- setosa[sample(nrow(setosa), 20),]

versicolor <- unk[species=="versicolor",]
versicolor <- versicolor[sample(nrow(versicolor), 20),]

virginica <- unk[species=="virginica",]
virginica <- virginica[sample(nrow(virginica), 20),]

p <- predict(som, unk)
head(p)

## plot:
plot(som)
dev.off()
plot(som, predict = som@predict(setosa))
plot(som, predict = som@predict(versicolor), add = TRUE, pch.col = "magenta", pch = 17)
plot(som, predict = som@predict(virginica), add = TRUE, pch.col = "white", pch = 8)

som.nn documentation built on May 2, 2019, 8:26 a.m.