nlp_perceptron: Spark NLP Perceptron
In r-spark/sparknlp: R Interface to John Snow Labs Spark NLP

nlp_perceptron

R Documentation

Spark NLP Perceptron

Spark ML transformer that sets a POS tag to each word within a sentence. Its train data (train_pos) is a spark dataset of POS format values with Annotation columns. See https://nlp.johnsnowlabs.com/docs/en/annotators#postagger

nlp_perceptron(
  x,
  input_cols,
  output_col,
  n_iterations = NULL,
  pos_column = NULL,
  uid = random_string("perceptron_")
)

`x`	A `spark_connection`, `ml_pipeline`, or a `tbl_spark`.
`input_cols`	Input columns. String array.
`output_col`	Output column. String.
`n_iterations`	Number of iterations for training. May improve accuracy but takes longer. Default 5.
`pos_column`	Column containing an array of POS Tags matching every token on the line.
`uid`	A character string used to uniquely identify the ML estimator.

The object returned depends on the class of x.

spark_connection: When x is a spark_connection, the function returns an instance of a ml_estimator object. The object contains a pointer to a Spark 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 a default pretrained NLP model appended to the pipeline.
tbl_spark: When x is a tbl_spark, an estimator is constructed then immediately fit with the input tbl_spark, returning an NLP model.