ml_lda
From sparklyr v0.2.30
by Javier Luraschi
Spark ML -- Latent Dirichlet Allocation
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
Community examples
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