ml_kmeans

0th

Percentile

Spark ML -- K-Means Clustering

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

Aliases
  • ml_kmeans
Documentation reproduced from package sparklyr, version 0.3.1, License: file LICENSE

Community examples

Looks like there are no examples yet.