nlp_classifier_dl: Spark NLP ClassifierDLApproach

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

Spark NLP ClassifierDLApproach

Description

Spark ML annotator that See https://nlp.johnsnowlabs.com/docs/en/annotators#classifierdl

Usage

nlp_classifier_dl(
  x,
  input_cols,
  output_col,
  label_col,
  batch_size = NULL,
  max_epochs = NULL,
  lr = NULL,
  dropout = NULL,
  validation_split = NULL,
  verbose = NULL,
  enable_output_logs = NULL,
  lazy_annotator = NULL,
  output_logs_path = NULL,
  uid = random_string("classifier_dl_")
)

Arguments

x	A spark_connection, ml_pipeline, or a tbl_spark.
input_cols	Input columns. String array.
output_col	Output column. String.
label_col	name of the column containing the category labels
batch_size	Batch size for training
max_epochs	Maximum number of epochs to train
lr	Initial learning rate
dropout	Dropout coefficient
validation_split	proportion of data to split off for validation
verbose	Verbosity level
enable_output_logs	boolean to enable/disable output logs
lazy_annotator	boolean
output_logs_path	path to put the output logs
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.