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