ft_string_indexer {sparklyr}

Feature Transformation – StringIndexer (Estimator)

Description

A label indexer that maps a string column of labels to an ML column of label indices. If the input column is numeric, we cast it to string and index the string values. The indices are in [0, numLabels), ordered by label frequencies. So the most frequent label gets index 0. This function is the inverse of ft_index_to_string.

Usage

ft_string_indexer(
  x,
  input_col = NULL,
  output_col = NULL,
  handle_invalid = "error",
  string_order_type = "frequencyDesc",
  uid = random_string("string_indexer_"),
  ...
)

ml_labels(model)

ft_string_indexer_model(
  x,
  input_col = NULL,
  output_col = NULL,
  labels,
  handle_invalid = "error",
  uid = random_string("string_indexer_model_"),
  ...
)

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"

string_order_type

(Spark 2.3+)How to order labels of string column. The first label after ordering is assigned an index of 0. Options are "frequencyDesc", "frequencyAsc", "alphabetDesc", and "alphabetAsc". Defaults to "frequencyDesc".

uid

A character string used to uniquely identify the feature transformer.

...

Optional arguments; currently unused.

model

A fitted StringIndexer model returned by ft_string_indexer()

labels

Vector of labels, corresponding to indices to be assigned.

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.

ml_labels() returns a vector of labels, corresponding to indices to be assigned.

See Also

ft_index_to_string

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_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_tokenizer(), ft_vector_assembler(), ft_vector_indexer(), ft_vector_slicer(), ft_word2vec()