Feature Transformation -- VectorAssembler

Combine multiple vectors into a single row-vector; that is, where each row element of the newly generated column is a vector formed by concatenating each row element from the specified input columns.

ft_vector_assembler(x, input.col, output.col, ...)

Arguments

x

An object (usually a spark_tbl) coercable to a Spark DataFrame.

input.col

The name of the input column(s).

output.col

The name of the output column.

...

Optional arguments; currently unused.

See also

See http://spark.apache.org/docs/latest/ml-features for more information on the set of transformations available for DataFrame columns in Spark.

Other feature transformation routines: ft_binarizer, ft_bucketizer, ft_count_vectorizer, ft_discrete_cosine_transform, ft_elementwise_product, ft_index_to_string, ft_one_hot_encoder, ft_quantile_discretizer, ft_regex_tokenizer, ft_stop_words_remover, ft_string_indexer, ft_tokenizer, sdf_mutate