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

nlp_multi_classifier_dl

R Documentation

Spark NLP MultiClassifierDLApproach

Description

Spark ML estimator that See https://nlp.johnsnowlabs.com/docs/en/annotators#multiclassifierdl-multi-label-text-classification

Usage

nlp_multi_classifier_dl(
  x,
  input_cols,
  output_col,
  batch_size = NULL,
  enable_output_logs = NULL,
  label_col = NULL,
  lr = NULL,
  max_epochs = NULL,
  output_logs_path = NULL,
  shuffle_per_epoch = NULL,
  threshold = NULL,
  validation_split = NULL,
  verbose = NULL,
  uid = random_string("multi_classifier_dl_")
)

Arguments

`x`	A `spark_connection`, `ml_pipeline`, or a `tbl_spark`.
`input_cols`	Input columns. String array.
`output_col`	Output column. String.
`batch_size`	Batch size
`enable_output_logs`	whether to output to annotators log folder
`label_col`	column with label per each document
`lr`	learning rate
`max_epochs`	maximum number of epoch to train
`output_logs_path`	output logs path
`shuffle_per_epoch`	shuffle per epoch
`threshold`	the minimum threshold for each label to be accepted
`validation_split`	choose the proportion of training dataset to be validated against the model on each epoch
`verbose`	level of verbosity during training (integer)
`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.