nlp_document_logreg_classifier: Spark NLP DocumentLogRegClassifierApproach

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

Spark NLP DocumentLogRegClassifierApproach

Description

Spark ML estimator that See https://nlp.johnsnowlabs.com/licensed/api/com/johnsnowlabs/nlp/annotators/classification/DocumentLogRegClassifierApproach.html

Usage

nlp_document_logreg_classifier(
  x,
  input_cols,
  output_col,
  fit_intercept = NULL,
  label_column = NULL,
  labels = NULL,
  max_iter = NULL,
  merge_chunks = NULL,
  tol = NULL,
  uid = random_string("document_logreg_classifier_")
)

Arguments

x	A spark_connection, ml_pipeline, or a tbl_spark.
input_cols	Input columns. String array.
output_col	Output column. String.
fit_intercept	whether to fit an intercept term (Default: true)
label_column	column with the value result we are trying to predict.
labels	array to output the label in the original form.
max_iter	maximum number of iterations (Default: 10)
merge_chunks	whether to merge all chunks in a document or not (Default: false)
tol	convergence tolerance after each iteration (Default: 1e-6)
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.