map.predict: Compute Classification Labels for Given Points

In popsom: An Efficient Implementation of Kohonen's Self-Organizing Maps (SOMs) with Starburst Visualizations

Description

Compute classification labels for points in a given data frame using the underlying clustering model. If the training data is unlabeled then machine-generated labels are used.

Usage

map.predict(map,points)

Arguments

map	An object of type 'map'.
points	A data frame of points to be classified.

Value

A data frame with classification results. The data frame has two columns:

Label

The assigned label to the observation at the same row in the 'points' data frame.

Confidence

A confidence value assigned to the label prediction.

Author(s)

Lutz Hamel

Examples

data(iris)

df <- subset(iris,select=-Species)
labels <- subset(iris,select=Species)

m <- map.build(df,labels,xdim=15,ydim=10,train=10000)

map.predict(m,df)

popsom documentation built on Dec. 21, 2021, 1:07 a.m.