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.

ft_binarizer(x, input.col = NULL, output.col = NULL, threshold = 0.5, ...)

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.

threshold

The numeric threshold.

...

Optional arguments; currently unused.

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_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_sql_transformer, ft_string_indexer, ft_tokenizer, ft_vector_assembler, sdf_mutate