Package: clustRcompaR
Type: Package
Title: Easy Interface for Clustering a Set of Documents and Exploring
        Group- Based Patterns
Version: 0.1.0
Date: 2017-01-06
Author: Josh 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. http://dx.doi.org/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, tidyr
VignetteBuilder: knitr
Suggests: knitr, rmarkdown
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2017-01-06 19:59:18 UTC; joshuarosenberg
Repository: CRAN
Date/Publication: 2017-01-07 02:27:49
