Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!
Get Started for Free

predict

Model Predictions


Description

Provides the S4 method predict for itemMatrix (e.g., transactions). Predicts the membership (nearest neighbor) of new data to clusters represented by medoids or labeled examples.

Usage

## S4 method for signature 'itemMatrix'
predict(object, newdata, labels = NULL, blocksize = 200,...)

Arguments

object

medoids (no labels needed) or examples (labels needed).

newdata

objects to predict labels for.

labels

an integer vector containing the labels for the examples in object.

blocksize

a numeric scalar indicating how much memory predict can use for big x and/or y (approx. in MB). This is only a crude approximation for 32-bit machines (64-bit architectures need double the blocksize in memory) and using the default Jaccard method for dissimilarity calculation. In general, reducing blocksize will decrease the memory usage but will increase the run-time.

...

further arguments passed on to dissimilarity. E.g., method.

Value

An integer vector of the same length as newdata containing the predicted labels for each element.

Author(s)

Michael Hahsler

See Also

Examples

data("Adult")

## sample
small <- sample(Adult, 500)
large <- sample(Adult, 5000)

## cluster a small sample
d_jaccard <- dissimilarity(small)
hc <- hclust(d_jaccard)
l <-  cutree(hc, k=4)

## predict labels for a larger sample
labels <- predict(small, large, l)


## plot the profile of the 1. cluster
itemFrequencyPlot(large[labels==1, itemFrequency(large) > 0.1])

arules

Mining Association Rules and Frequent Itemsets

v1.6-7
GPL-3
Authors
Michael Hahsler [aut, cre, cph], Christian Buchta [aut, cph], Bettina Gruen [aut, cph], Kurt Hornik [aut, cph], Ian Johnson [ctb, cph], Christian Borgelt [ctb, cph]
Initial release
2021-03-12

We don't support your browser anymore

Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.