R: Correspondence analysis of a document-feature matrix

textmodel_ca {quanteda.textmodels} | R Documentation

## Correspondence analysis of a document-feature matrix

### Description

`textmodel_ca` implements correspondence analysis scaling on a dfm. The method is a fast/sparse version of function ca.

### Usage

    textmodel_ca(x, smooth = 0, nd = NA, sparse = FALSE, residual_floor = 0.1)

### Arguments

`x` | the dfm on which the model will be fit
`smooth` | a smoothing parameter for word counts; defaults to zero.
`nd` | Number of dimensions to be included in output; if `NA` (the default) then the maximum possible dimensions are included.
`sparse` | retains the sparsity if set to `TRUE`; set it to `TRUE` if `x` (the dfm) is too big to be allocated after converting to dense
`residual_floor` | specifies the threshold for the residual matrix for calculating the truncated svd.Larger value will reduce memory and time cost but might reduce accuracy; only applicable when `sparse = TRUE`

### Details

svds in the RSpectra package is applied to enable the fast computation of the SVD.

### Value

`textmodel_ca()` returns a fitted CA textmodel that is a special class of ca object.

### Note

You may need to set `sparse = TRUE`) and increase the value of `residual_floor` to ignore less important information and hence to reduce the memory cost when you have a very big dfm. If your attempt to fit the model fails due to the matrix being too large, this is probably because of the memory demands of computing the V \times V residual matrix. To avoid this, consider increasing the value of `residual_floor` by 0.1, until the model can be fit.

### Author(s)

Kenneth Benoit and Haiyan Wang

### References

Nenadic, O. & Greenacre, M. (2007). Correspondence Analysis in R, with Two- and Three-dimensional Graphics: The ca package. Journal of Statistical Software, 20(3).

### See Also

`coef.textmodel_lsa()`, ca

### Examples

    library("quanteda")
    dfmat <- dfm(tokens(data_corpus_irishbudget2010))
    tmod <- textmodel_ca(dfmat)
    summary(tmod)

[Package quanteda.textmodels version 0.9.4 Index]