
Cluster prediction for multivariate observations based on Gaussian finite mixture models estimated by Mclust
.
# S3 method for Mclust
predict(object, newdata, …)
an object of class 'Mclust'
resulting from a call to Mclust
.
a data frame or matrix giving the data. If missing the clustering data obtained from the call to Mclust
are classified.
further arguments passed to or from other methods.
Returns a list of with the following components:
a factor of predicted cluster labels for newdata
.
a matrix whose [i,k]th entry is the probability that
observation i in newdata
belongs to the kth cluster.
# NOT RUN {
model <- Mclust(faithful)
# predict cluster for the observed data
pred <- predict(model)
str(pred)
pred$z # equal to model$z
pred$classification # equal to
plot(faithful, col = pred$classification, pch = pred$classification)
# predict cluster over a grid
grid <- apply(faithful, 2, function(x) seq(min(x), max(x), length = 50))
grid <- expand.grid(eruptions = grid[,1], waiting = grid[,2])
pred <- predict(model, grid)
plot(grid, col = mclust.options("classPlotColors")[pred$classification], pch = 15, cex = 0.5)
points(faithful, pch = model$classification)
# }
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