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View Code? Open in Web Editor NEWEasy, fast clustering of texts
Easy, fast clustering of texts
With the focus of text analysis on building a matrix of the right features many features will come from things other than the words themselves. Many packages in my framework will be able to be converted to dtm. It'd be prudent to allow them to be joined together and make the dtm in the data_store
Add an n loop iterative
partition that splits of the large mass into k clusters. There'd be an argument to pass n length vector of k splits. Not sure if this is a separate function after xxx_cluster
. This seems to be the most sense.
ALTERNATIVE...
Investigate dynamic tree cut: https://labs.genetics.ucla.edu/horvath/CoexpressionNetwork/WORKSHOP/2013/LectureHierarchicalClusteringLangfelder1.pdf
https://labs.genetics.ucla.edu/horvath/CoexpressionNetwork/BranchCutting/Supplement.pdf
https://cran.r-project.org/web/packages/dynamicTreeCut/
https://labs.genetics.ucla.edu/horvath/CoexpressionNetwork/BranchCutting/
This might require a tree object and may not be usable by all clustering algorithms.
## Answer to http://stackoverflow.com/q/22936951/1000343
dat <- data.frame(
person = LETTERS[1:3],
text = c("Best way to waste money", "Amazing stuff. lets you stay connected all the time", "Instrument to waste money and time"),
stringsAsFactors = FALSE
)
x <- with(
dat,
data_store(text, person)
)
hierarchical_cluster(x) %>%
plot(h=.9, lwd=2)
hierarchical_cluster(x) %>%
assign_cluster(h=.9)
hierarchical_cluster(x) %>%
assign_cluster(h=.9) %>%
get_terms()
hierarchical_cluster(x) %>%
assign_cluster(h=.9) %>%
get_documents()
To get rid of message add by = "id_temporary"
to the dplyr::join
Run all or multiple of the algorithms and then using a collocation of element assignment groups elements together. This may allow for multiple groups assignments.
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