skmeans_cluster: Fit a skmean Cluster

In trinker/clustext: Consistent Clustering for Text Data

Description

Fit a skmean cluster to text data. Prior to distance measures being calculated the tf-idf (see weightTfIdf) is applied to the DocumentTermMatrix. Cosine dissimilarity is used to generate the distance matrix supplied to skmeans.

Usage

skmeans_cluster(x, k, ...)

## S3 method for class 'data_store'
skmeans_cluster(x, k, ...)

Arguments

x	A data store object (see data_store).
k	The number of clusters.
...	Other arguments passed to skmeans.

Value

Returns an object of class "skmean".

Examples

library(dplyr)

x <- with(
    presidential_debates_2012,
    data_store(dialogue, paste(person, time, sep = "_"))
)


## 6 topic model
myfit1 <- skmeans_cluster(x, k=6)

myfit1 %>%
    assign_cluster()

myfit1 %>%
    assign_cluster() %>%
    summary()

## Not run: 
x2 <- presidential_debates_2012 %>%
    with(data_store(dialogue))

myfit2 <- skmeans_cluster(x2, 55)

assign_cluster(myfit2)

assign_cluster(myfit2) %>%
    summary()

## End(Not run)

trinker/clustext documentation built on May 31, 2019, 8:41 p.m.