cluster_classify {GSgalgoR} | R Documentation |
Given an n x m matrix of centroids, where m are the prototypic centroids with n features, classify new samples according to the distance to the centroids.
cluster_classify(data, centroid, method = "pearson")
data |
a |
centroid |
a |
method |
Character string indicating which method to use to calculate
distance to centroid. Options are |
Returns a numeric vector of length p with the class assigned to each sample according to the shortest distance to centroid
# load example dataset require(iC10TrainingData) require(pamr) data(train.Exp) data(IntClustMemb) TrainData <- list(x = train.Exp, y = IntClustMemb) # Create prototypic centroids pam <- pamr.train(TrainData) centroids <- pam$centroids Class <- cluster_classify(train.Exp, centroids) table(Class, IntClustMemb)