ft_one_hot_encoder
Feature Transformation -- OneHotEncoder (Transformer)
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_col = NULL, output_col = NULL,
drop_last = TRUE, uid = random_string("one_hot_encoder_"), ...)Arguments
- x
A
spark_connection,ml_pipeline, or atbl_spark.- input_col
The name of the input column.
- output_col
The name of the output column.
- 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: Whenxis aspark_connection, the function returns aml_transformer, aml_estimator, or one of their subclasses. The object contains a pointer to a SparkTransformerorEstimatorobject and can be used to composePipelineobjects.ml_pipeline: Whenxis aml_pipeline, the function returns aml_pipelinewith the transformer or estimator appended to the pipeline.tbl_spark: Whenxis atbl_spark, a transformer is constructed then immediately applied to the inputtbl_spark, returning atbl_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_pca,
ft_polynomial_expansion,
ft_quantile_discretizer,
ft_r_formula,
ft_regex_tokenizer,
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