ml_als_factorization(x, rating.column = "rating", user.column = "user", item.column = "item", rank = 10L, regularization.parameter = 0.1, iter.max = 10L, ml.options = ml_options(), ...)
tbl_spark
).ml_options
for more details.data
argument can be used to
specify the data to be used when x
is a formula; this allows calls
of the form ml_linear_regression(y ~ x, data = tbl)
, and is
especially useful in conjunction with do
.ml_decision_tree
,
ml_generalized_linear_regression
,
ml_gradient_boosted_trees
,
ml_kmeans
, 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