clean_data: Structure Data

In activetext/activeR: a semi-supervised active learning algorithm for text classification.

Structure Data

Description

Structures data to prepare for Active-EM implementation. Options to filter documents by chosen character strings, as well as to add index value for each document.

Usage

clean_data(
  docs,
  n_class,
  doc_name,
  index_name,
  labels_name = NULL,
  filters = NULL,
  add_index = T,
  add_filter = T,
  keep_labels = F
)

Arguments

docs	[matrix] Matrix of labeled and/or unlabeled documents.
n_class	[numeric] Number of classes to be considered.
doc_name	[string] Character string indicating the variable in 'docs' that denotes the text of the documents to be classified.
index_name	[character] Character string indicating the variable in 'docs' that denotes the index value of the document to be classified.
labels_name	[character] Character string indicating the variable in docs that denotes the already known labels of the documents. By default, value is set to NULL.
filters	[character] A vector of regular expressions used to filter out unwanted documents.
add_index	[logical] Boolean logical value indicating whether or not add an index in the restructuring process.
add_filter	[logical] Boolean logical value indicating whether or not to filter documents in the restructuring process.
keep_labels	[logical] Boolean logical value indicating whether or not to keep an existing column of labels in the dataset.

Value

[matrix] Structured matrix of labeled and unlabeled documents, updated with labels for the documents in 'toLabel'.

activetext/activeR documentation built on May 31, 2024, 10:21 a.m.