ft_elementwise_product
From sparklyr v0.3.3
by Javier Luraschi
Feature Transformation -- ElementwiseProduct
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.
Usage
ft_elementwise_product(x, input_col = NULL, output_col = NULL, scaling_col)
Arguments
- x
- An object (usually a
spark_tbl
) coercable to a Spark DataFrame. - input_col
- The name of the input column(s).
- output_col
- The name of the output column.
- scaling_col
- The column used to scale
input_col
.
See Also
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_sql_transformer
,
ft_string_indexer
,
ft_vector_assembler
,
sdf_mutate
Community examples
Looks like there are no examples yet.