R: Predict method for Correlated topic models (CTM)

predict.ctm_topic_model {textmineR} | R Documentation

## Predict method for Correlated topic models (CTM)

### Description

Obtains predictions of topics for new documents from a fitted CTM model

### Usage

    ## S3 method for class 'ctm_topic_model'
    predict(object, newdata, ...)

### Arguments

`object` | a fitted object of class "ctm_topic_model"
`newdata` | a DTM or TCM of class dgCMatrix or a numeric vector
`...` | further arguments passed to or from other methods.

### Value

a "theta" matrix with one row per document and one column per topic

### Note

Predictions for this method are performed using the "dot" method as described in the textmineR vignette "c_topic_modeling".

### Examples

    # Load a pre-formatted dtm
    ## Not run:
    data(nih_sample_dtm)

    model <- FitCtmModel(dtm = nih_sample_dtm[1:20,], k = 3,
                         calc_coherence = FALSE, calc_r2 = FALSE)

    # Get predictions on the next 50 documents
    pred <- predict(model, nih_sample_dtm[21:100,])

    ## End(Not run)

[Package textmineR version 3.0.5 Index]