A regex based tokenizer that extracts tokens either by using the provided
regex pattern to split the text (default) or repeatedly matching the regex
(if gaps is false). Optional parameters also allow filtering tokens using a
minimal length. It returns an array of strings that can be empty.
ft_regex_tokenizer(x, input_col, output_col, gaps = TRUE,
min_token_length = 1L, pattern = "\\s+", to_lower_case = TRUE,
uid = random_string("regex_tokenizer_"), ...)A spark_connection, ml_pipeline, or a tbl_spark.
The name of the input column.
The name of the output column.
Indicates whether regex splits on gaps (TRUE) or matches tokens (FALSE).
Minimum token length, greater than or equal to 0.
The regular expression pattern to be used.
Indicates whether to convert all characters to lowercase before tokenizing.
A character string used to uniquely identify the feature transformer.
Optional arguments; currently unused.
The object returned depends on the class of x.
spark_connection: When x is a spark_connection, the function returns a ml_transformer,
a ml_estimator, or one of their subclasses. The object contains a pointer to
a Spark Transformer or Estimator object and can be used to compose
Pipeline objects.
ml_pipeline: When x is a ml_pipeline, the function returns a ml_pipeline with
the transformer or estimator appended to the pipeline.
tbl_spark: When x is a tbl_spark, a transformer is constructed then
immediately applied to the input tbl_spark, returning a tbl_spark
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 transformers: ft_binarizer,
ft_bucketizer,
ft_chisq_selector,
ft_count_vectorizer, ft_dct,
ft_elementwise_product,
ft_feature_hasher,
ft_hashing_tf, ft_idf,
ft_imputer,
ft_index_to_string,
ft_interaction, ft_lsh,
ft_max_abs_scaler,
ft_min_max_scaler, ft_ngram,
ft_normalizer,
ft_one_hot_encoder, ft_pca,
ft_polynomial_expansion,
ft_quantile_discretizer,
ft_r_formula,
ft_sql_transformer,
ft_standard_scaler,
ft_stop_words_remover,
ft_string_indexer,
ft_tokenizer,
ft_vector_assembler,
ft_vector_indexer,
ft_vector_slicer, ft_word2vec