ft_vector_indexer: Feature Transformation - VectorIndexer (Estimator)

View source: R/ml_feature_vector_indexer.R

ft_vector_indexerR Documentation

Feature Transformation – VectorIndexer (Estimator)

Description

Indexing categorical feature columns in a dataset of Vector.

Usage

ft_vector_indexer(
  x,
  input_col = NULL,
  output_col = NULL,
  handle_invalid = "error",
  max_categories = 20,
  uid = random_string("vector_indexer_"),
  ...
)

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.

handle_invalid

(Spark 2.1.0+) Param for how to handle invalid entries. Options are 'skip' (filter out rows with invalid values), 'error' (throw an error), or 'keep' (keep invalid values in a special additional bucket). Default: "error"

max_categories

Threshold for the number of values a categorical feature can take. If a feature is found to have > max_categories values, then it is declared continuous. Must be greater than or equal to 2. Defaults to 20.

uid

A character string used to uniquely identify the feature transformer.

...

Optional arguments; currently unused.

Details

In the case where x is a tbl_spark, the estimator fits against x to obtain a transformer, returning a tbl_spark.

Value

The object returned depends on the class of x. If it is a spark_connection, the function returns a ml_estimator or a ml_estimator object. If it is a ml_pipeline, it will return a pipeline with the transformer or estimator appended to it. If a tbl_spark, it will return a tbl_spark with the transformation applied to it.

See Also

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_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_slicer(), ft_word2vec()


rstudio/sparklyr documentation built on March 23, 2024, 2:29 p.m.