Pick the optimal label from candidate labels
pickLabel(
n,
text.predict = NULL,
text.name = "text",
top1.name = "top1",
labels.index = NULL,
candidate.labels = NULL
)A matrix with n rows and 6 columns (topic, doc, opt1, opt2, opt3, optcrt) where optcrt is the correct label that was picked.
The number of desired tasks
A data frame or matrix containing both the text and the indicator(s) of the model predicted topic(s).
variable name in `text.predict` that indicates the text
variable name in `text.predict` that indicates the top1 model predicted topic
The topic index in correspondence with the labels, e.g., c(10, 12, 15).
A list of vectors containing the user-defined labels assigned to the topics, Must be in the same length and order with `labels.index`.
Users need to specify four plausible labels for each topic