predict.textreg.result: Predict labeling with the selected phrases.

In textreg: n-Gram Text Regression, aka Concise Comparative Summarization

Description

Given raw text and a textreg model, predict the labeling by counting appearance of relevant phrases in text and then multiplying these counts by the beta vector associated with the textreg object. Just like linear regression.

Usage

## S3 method for class 'textreg.result'
predict(object, new.text = NULL,
  return.matrix = FALSE, ...)

Arguments

object	A textreg.result object
new.text	If you want to predict for new text, pass it along.
return.matrix	TRUE means hand back the phrase appearance pattern matrix.
...	Nothing can be passed extra.

Value

Vector of predictions (numbers).

Examples

res = textreg( c( "", "", "A", "A" ), c( -1, -1, 1, 1 ), 
      C=1, Lq=1, convergence.threshold=0.00000001, verbosity=0 )
predict( res )
predict( res, new.text=c("A B C A") )

textreg documentation built on May 2, 2019, 8:34 a.m.