predict.textmodel_wordscores: Predict textmodel_wordscores

In quanteda.textmodels: Scaling Models and Classifiers for Textual Data

Predict textmodel_wordscores

Description

Predict textmodel_wordscores

Usage

## S3 method for class 'textmodel_wordscores'
predict(
  object,
  newdata = NULL,
  se.fit = FALSE,
  interval = c("none", "confidence"),
  level = 0.95,
  rescaling = c("none", "lbg", "mv"),
  force = TRUE,
  ...
)

Arguments

object	a fitted Wordscores textmodel
newdata	dfm on which prediction should be made
se.fit	if TRUE, return standard errors as well
interval	type of confidence interval calculation
level	tolerance/confidence level for intervals
rescaling	"none" for "raw" scores; "lbg" for LBG (2003) rescaling; or "mv" for the rescaling proposed by Martin and Vanberg (2007). See References.
force	make the feature set of newdata conform to the model terms. The default of TRUE means that a fitted model can be applied to scale a dfm that does not contain a 1:1 match of features in the training and prediction data.
...	not used

Value

predict.textmodel_wordscores() returns a named vector of predicted document scores ("text scores" S_{vd} in LBG 2003), or a named list if se.fit = TRUE consisting of the predicted scores (⁠$fit⁠) and the associated standard errors (⁠$se.fit⁠). When interval = "confidence", the predicted values will be a matrix. This behaviour matches that of stats::predict.lm().

Examples

tmod <- textmodel_wordscores(quanteda::data_dfm_lbgexample, c(seq(-1.5, 1.5, .75), NA))
predict(tmod)
predict(tmod, rescaling = "mv")
predict(tmod, rescaling = "lbg")
predict(tmod, se.fit = TRUE)
predict(tmod, se.fit = TRUE, interval = "confidence")
predict(tmod, se.fit = TRUE, interval = "confidence", rescaling = "lbg")

quanteda.textmodels documentation built on March 31, 2023, 8:09 p.m.