Similar to R's cut function, this transforms a numeric column
into a discretized column, with breaks specified through the splits
parameter.
ft_bucketizer(x, input.col = NULL, output.col = NULL, splits, ...)An object (usually a spark_tbl) coercable to a Spark DataFrame.
The name of the input column(s).
The name of the output column.
A numeric vector of cutpoints, indicating the bucket boundaries.
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_discrete_cosine_transform,
ft_elementwise_product,
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