validateLabel: Create validation tasks for labels assigned to the topics in...

In Luwei-Ying/validateIt: Validating Topic Coherence and Topic Labels

Description

Create validation tasks for labels assigned to the topics in the topic model of choice.

Usage

validateLabel(
  type,
  n,
  text.predict = NULL,
  text.name = "text",
  top1.name = "top1",
  top2.name = "top2",
  top3.name = "top3",
  labels = NULL,
  labels.index = NULL,
  labels.add = NULL
)

Arguments

type	Task structures to be specified. Must be one of "LI" (Label Intrusion) and "OL" (Optimal Label).
n	The number of desired tasks
text.predict	A data frame or matrix containing both the text and the indicator(s) of the model predicted topic(s).
text.name	variable name in 'text.predict' that indicates the text
top1.name	variable name in 'text.predict' that indicates the top1 model predicted topic
top2.name	variable name in 'text.predict' that indicates the top2 model predicted topic
top3.name	variable name in 'text.predict' that indicates the top3 model predicted topic
labels	The user-defined labels assigned to the topics
labels.index	The topic index in correspondence with the labels, e.g., c(10, 12, 15). Must be in the same length and order with 'label'.
labels.add	Labels from other broad catagories. Default to NULL. Users could specify them to evaluate how well different broad categories are distinguished from one another.

Details

Users need to pick a topic model that they deem to be good and label the topics they later would like to use as measures.

Luwei-Ying/validateIt documentation built on May 12, 2021, 9:43 p.m.