nlp_sentence_detector_dl: Spark NLP SentenceDetectorDLApproach

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

Spark NLP SentenceDetectorDLApproach

Description

Spark ML estimator that See https://nlp.johnsnowlabs.com/docs/en/annotators

Usage

nlp_sentence_detector_dl(
  x,
  input_cols,
  output_col,
  epochs_number = NULL,
  impossible_penultimates = NULL,
  model = NULL,
  output_logs_path = NULL,
  validation_split = NULL,
  explode_sentences = NULL,
  uid = random_string("sentence_detector_dl_")
)

Arguments

x	A spark_connection, ml_pipeline, or a tbl_spark.
input_cols	Input columns. String array.
output_col	Output column. String.
epochs_number	maximum number of epochs to train
impossible_penultimates	impossible penultimates
model	model architecture
output_logs_path	path to folder to output logs
validation_split	choose the proportion of training dataset to be validated agaisnt the model on each epoch
explode_sentences	a flag indicating whether to split sentences into different Dataset rows.
uid	A character string used to uniquely identify the ML estimator.

Value

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 the NLP estimator 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.

r-spark/sparknlp documentation built on Oct. 15, 2022, 10:50 a.m.