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.
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_"),
...
)
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.
A spark_connection, ml_pipeline, or a tbl_spark.
The name of the input column.
The name of the output column.
(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"
(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".
A character string used to uniquely identify the feature transformer.
Optional arguments; currently unused.
A fitted StringIndexer model returned by ft_string_indexer()
Vector of labels, corresponding to indices to be assigned.
In the case where x is a tbl_spark, the estimator
fits against x to obtain a transformer, returning a tbl_spark.
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_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_tokenizer(),
ft_vector_assembler(),
ft_vector_indexer(),
ft_vector_slicer(),
ft_word2vec()