predict.textmodel_nb: Prediction from a fitted textmodel_nb object

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

Prediction from a fitted textmodel_nb object

Description

predict.textmodel_nb() implements class predictions from a fitted Naive Bayes model. using trained Naive Bayes examples

Usage

## S3 method for class 'textmodel_nb'
predict(
  object,
  newdata = NULL,
  type = c("class", "probability", "logposterior"),
  force = FALSE,
  ...
)

## S3 method for class 'textmodel_nb'
coef(object, ...)

## S3 method for class 'textmodel_nb'
coefficients(object, ...)

Arguments

object	a fitted Naive Bayes textmodel
newdata	dfm on which prediction should be made
type	the type of predicted values to be returned; see Value
force	make newdata's feature set conformant to the model terms
...	not used

Value

predict.textmodel_nb returns either a vector of class predictions for each row of newdata (when type = "class"), or a document-by-class matrix of class probabilities (when type = "probability") or log posterior likelihoods (when type = "logposterior").

coef.textmodel_nb() returns a matrix of estimated word likelihoods given the class. (In earlier versions, this was named PwGc.)

See Also

textmodel_nb()

Examples

# application to LBG (2003) example data
(tmod <- textmodel_nb(quanteda::data_dfm_lbgexample, y = c("A", "A", "B", "C", "C", NA)))
predict(tmod)
predict(tmod, type = "logposterior")

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