R: [Experimental] Compute document/feature proximity

textstat_proxy {quanteda.textstats} | R Documentation

## [Experimental] Compute document/feature proximity

### Description

This is an underlying function for `textstat_dist` and `textstat_simil` but returns `TsparseMatrix`.

### Usage

    textstat_proxy(
      x,
      y = NULL,
      margin = c("documents", "features"),
      method = c("cosine", "correlation", "jaccard", "ejaccard", "dice", "edice", "hamman",
        "simple matching", "euclidean", "chisquared", "hamming", "kullback", "manhattan",
        "maximum", "canberra", "minkowski"),
      p = 2,
      min_proxy = NULL,
      rank = NULL,
      use_na = FALSE
    )

### Arguments

`x` | a dfm objects; `y` is an optional target matrix matching `x` in the margin on which the similarity or distance will be computed.
`y` | if a dfm object is provided, proximity between documents or features in `x` and `y` is computed.
`margin` | identifies the margin of the dfm on which similarity or difference will be computed: `"documents"` for documents or `"features"` for word/term features.
`method` | character; the method identifying the similarity or distance measure to be used; see Details.
`p` | The power of the Minkowski distance.
`min_proxy` | the minimum proximity value to be recoded.
`rank` | an integer value specifying top-n most proximity values to be recorded.
`use_na` | if `TRUE`, return `NA` for proximity to empty vectors. Note that use of `NA` makes the proximity matrices denser.

### See Also

`textstat_dist()`, `textstat_simil()`

[Package quanteda.textstats version 0.94.1 Index]