Computes the element-wise product between two columns. Generally, this is intended as a scaling transformation, where an input vector is scaled by another vector, but this should apply for all element-wise product transformations.
ft_elementwise_product(x, input.col = NULL, output.col = NULL, scaling.col,
...)
An object (usually a spark_tbl
) coercable to a Spark DataFrame.
The name of the input column(s).
The name of the output column.
The column used to scale input.col
.
Optional arguments; currently unused.
See http://spark.apache.org/docs/latest/ml-features.html for more information on the set of transformations available for DataFrame columns in Spark.
Other feature transformation routines: ft_binarizer
,
ft_bucketizer
,
ft_discrete_cosine_transform
,
ft_index_to_string
,
ft_one_hot_encoder
,
ft_quantile_discretizer
,
ft_regex_tokenizer
,
ft_sql_transformer
,
ft_string_indexer
,
ft_tokenizer
,
ft_vector_assembler
,
sdf_mutate