sparklyr (version 1.4.0)

ft_one_hot_encoder: Feature Transformation -- OneHotEncoder (Transformer)

Description

One-hot encoding maps a column of label indices to a column of binary vectors, with at most a single one-value. This encoding allows algorithms which expect continuous features, such as Logistic Regression, to use categorical features. Typically, used with ft_string_indexer() to index a column first.

Usage

ft_one_hot_encoder(
  x,
  input_cols = NULL,
  output_cols = NULL,
  handle_invalid = NULL,
  drop_last = TRUE,
  uid = random_string("one_hot_encoder_"),
  ...
)

Arguments

x

A spark_connection, ml_pipeline, or a tbl_spark.

input_cols

The name of the input columns.

output_cols

The name of the output columns.

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"

drop_last

Whether to drop the last category. Defaults to TRUE.

uid

A character string used to uniquely identify the feature transformer.

...

Optional arguments; currently unused.

Value

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 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_ngram(), ft_normalizer(), ft_one_hot_encoder_estimator(), 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()