Package: clustRcompaR
Type: Package
Title: Easy Interface for Clustering a Set of Documents and Exploring
        Group- Based Patterns
Version: 0.2.0
Date: 2018-01-23
Author: Joshua Rosenberg, Alex Lishinski
Maintainer: Alex Lishinski <alexlishinski@gmail.com>
Description: Provides an interface to perform cluster analysis on a corpus of
    text. Interfaces to Quanteda to assemble text corpuses easily. Deviationalizes
    text vectors prior to clustering using technique described by Sherin (Sherin,
    B. [2013]. A computational study of commonsense science: An exploration in the
    automated analysis of clinical interview data. Journal of the Learning Sciences,
    22(4), 600-638. Chicago. <doi:10.1080/10508406.2013.836654>). Uses
    cosine similarity as distance metric for two stage clustering process, involving
    Ward's algorithm hierarchical agglomerative clustering, and k-means clustering.
    Selects optimal number of clusters to maximize "variance explained" by clusters,
    adjusted by the number of clusters. Provides plotted output of clustering
    results as well as printed output. Assesses "model fit" of clustering solution
    to a set of preexisting groups in dataset.
License: GPL-3
Depends: R (>= 3.1.3),
URL: https://github.com/alishinski/clustRcompaR
Imports: quanteda, dplyr, ggplot2, ppls
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
RoxygenNote: 5.0.1
LazyData: true
NeedsCompilation: no
Packaged: 2018-01-28 19:56:04 UTC; alex
Repository: CRAN
Date/Publication: 2018-01-28 21:04:49
