sparklyr (version 0.3.1)

ml_kmeans: Spark ML -- K-Means Clustering

Description

Perform k-means clustering on a Spark DataFrame.

Usage

ml_kmeans(x, centers, max.iter = 100, features = dplyr::tbl_vars(x), ...)

Arguments

x

An object coercable to a Spark DataFrame (typically, a tbl_spark).

centers

The number of cluster centers to compute.

max.iter

The maximum number of iterations to use.

features

The name of features (terms) to use for the model fit.

...

Optional arguments; currently unused.

See Also

For information on how Spark k-means clustering is implemented, please see http://spark.apache.org/docs/latest/mllib-clustering.html#k-means.

Other Spark ML routines: ml_als_factorization, ml_decision_tree, ml_generalized_linear_regression, ml_gradient_boosted_trees, ml_lda, ml_linear_regression, ml_logistic_regression, ml_multilayer_perceptron, ml_naive_bayes, ml_one_vs_rest, ml_pca, ml_random_forest, ml_survival_regression