Apply thresholding to a column, such that values less than or equal to the
threshold are assigned the value 0.0, and values greater than the
threshold are assigned the value 1.0. Column output is numeric for
compatibility with other modeling functions.
ft_binarizer(x, input.col, output.col, threshold = 0.5, ...)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 numeric threshold.
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_bucketizer,
ft_count_vectorizer,
ft_discrete_cosine_transform,
ft_elementwise_product,
ft_index_to_string,
ft_one_hot_encoder,
ft_quantile_discretizer,
ft_regex_tokenizer,
ft_stop_words_remover,
ft_string_indexer,
ft_tokenizer,
ft_vector_assembler,
sdf_mutate