ft_ngram: Feature Transformation - NGram (Transformer)

Description Usage Arguments Details Value See Also

View source: R/ml_feature_ngram.R

Description

A feature transformer that converts the input array of strings into an array of n-grams. Null values in the input array are ignored. It returns an array of n-grams where each n-gram is represented by a space-separated string of words.

Usage

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ft_ngram(
  x,
  input_col = NULL,
  output_col = NULL,
  n = 2,
  uid = random_string("ngram_"),
  ...
)

Arguments

x

A spark_connection, ml_pipeline, or a tbl_spark.

input_col

The name of the input column.

output_col

The name of the output column.

n

Minimum n-gram length, greater than or equal to 1. Default: 2, bigram features

uid

A character string used to uniquely identify the feature transformer.

...

Optional arguments; currently unused.

Details

When the input is empty, an empty array is returned. When the input array length is less than n (number of elements per n-gram), no n-grams are returned.

Value

The object returned depends on the class of x.

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 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_normalizer(), ft_one_hot_encoder_estimator(), ft_one_hot_encoder(), ft_pca(), ft_polynomial_expansion(), ft_quantile_discretizer(), ft_r_formula(), ft_regex_tokenizer(), ft_robust_scaler(), 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()


sparklyr documentation built on June 17, 2021, 5:06 p.m.