categorize: Merge Clusters & Cluster Categories Back to Original Data

In trinker/clustext: Consistent Clustering for Text Data

Description

Merge clusters, categories, and the original data back together.

Usage

categorize(data, assign.cluster, cluster.key)

Arguments

data	A data set that was fit with a cluster model.
assign.cluster	An assign_cluster object.
cluster.key	An assign_cluster object.

Value

Returns a data.frame key of clusters and categories.

See Also

write_cluster_text, read_cluster_text

Examples

library(dplyr)

## Assign Clusters
ca <- presidential_debates_2012 %>%
    with(data_store(dialogue)) %>%
    hierarchical_cluster() %>%
    assign_cluster(k = 7)

## Write Cluster Text for Human Categorization
write_cluster_text(ca)
write_cluster_text(ca, n.sample=10)
write_cluster_text(ca, lead="  -", n.sample=10)

## Read Human Coded Categories Back In
categories_file <- system.file("additional/foo_turk.txt", package = "clustext")
readLines(categories_file)
(categories_key <- read_cluster_text(categories_file))

## Add Categories Back to Original Data Set
categorize(
    data = presidential_debates_2012,
    assign.cluster = ca,
    cluster.key = categories_key
)

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