sparklyr (version 0.2.30)

ml_lda: Spark ML -- Latent Dirichlet Allocation

Description

Fit a Latent Dirichlet Allocation (LDA) model to a Spark DataFrame.

Usage

ml_lda(x, features = dplyr::tbl_vars(x), k = length(features), ...)

Arguments

x

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

features

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

k

The number of topics to estimate.

...

Optional arguments; currently unused.

See Also

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