mergeTopics: Merge LDA Topic Matrices
In ldaPrototype: Prototype of Multiple Latent Dirichlet Allocation Runs

Description Usage Arguments Details Value See Also Examples

Generic function, which collects LDA results and merges their topic matrices for a given set of vocabularies.

1	mergeTopics(x, vocab, progress = TRUE)

`x`	[`named list`] `LDARep` or `LDABatch` object.
`vocab`	[`character`] Vocabularies taken into consideration for merging topic matrices.
`progress`	[`logical(1)`] Should a nice progress bar be shown? Turning it off, could lead to significantly faster calculation. Default ist `TRUE`.

This function uses the function mergeRepTopics or mergeBatchTopics. The topic matrices are transponed and cbinded, so that the resulting matrix contains the counts of vocabularies/words (row wise) in topics (column wise).

[named matrix] with the count of vocabularies (row wise) in topics (column wise).

Other merge functions: mergeBatchTopics(), mergeRepTopics()

Other workflow functions: LDARep(), SCLOP(), dendTopics(), getPrototype(), jaccardTopics()

res = LDARep(docs = reuters_docs, vocab = reuters_vocab, n = 4, K = 10, num.iterations = 30)
topics = mergeTopics(res, vocab = reuters_vocab)
dim(topics)
length(reuters_vocab)

## Not run: 
res = LDABatch(docs = reuters_docs, vocab = reuters_vocab, n = 4, K = 10, num.iterations = 30)
topics = mergeTopics(res, vocab = reuters_vocab)
dim(topics)
length(reuters_vocab)

## End(Not run)