predict.textmodel_affinity: Prediction for a fitted affinity textmodel

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

Description

Estimate θ_i for each document, from a fitted textmodel_affinity object.

Other methods below provide standard ways to extract or compute quantities from predicted textmodel_affinity objects.

Usage

## S3 method for class 'textmodel_affinity'
predict(object, newdata = NULL, level = 0.95, ...)

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

## S3 method for class 'predict.textmodel_affinity'
residuals(object, type = c("response", "pearson"), ...)

## S3 method for class 'predict.textmodel_affinity'
rstandard(model, ...)

Arguments

object	a fitted affinity textmodel
newdata	dfm on which prediction should be made
level	probability level for confidence interval width
...	unused
type	see residuals.lm

Value

predict() returns a list of predicted affinity textmodel quantities.

coef() returns a document \times class matrix of class affinities for each document.

residuals() returns a document-by-feature matrix of residuals. resid() is an alias.

rstandard() is a shortcut to return the pearson residuals.

See Also

influence.predict.textmodel_affinity() for methods of computing the influence of particular features from a predicted textmodel_affinity model.

quanteda.textmodels documentation built on April 6, 2021, 9:06 a.m.