Man pages for trinker/clustext
Consistent Clustering for Text Data
| approx_k | Approximate Number of Clusters for a Text Matrix |
| assign_cluster | Assign Clusters to Documents/Text Elements |
| assignments | Topic Assignments |
| as_topic | Convert 'get_terms' to Topics |
| categorize | Merge Clusters & Cluster Categories Back to Original Data |
| clustext | Consistent Clustering for Text Data |
| compare | Adjusted Rand Index Comaprison Between Algorithms |
| cosine_distance | Optimized Computation of Cosine Distance |
| data_store | Data Structure for 'hclusttext' |
| get_documents | Get Documents Based on Cluster Assignment in 'assign_cluster' |
| get_dtm | Get a 'DocumentTermMatrix' Stored in a 'hierarchical_cluster'... |
| get_removed | Get a Text Stored in a 'hierarchical_cluster' Object |
| get_terms | Get Terms Based on Cluster Assignment in 'assign_cluster' |
| get_text | Get a Text Stored in Various Objects |
| hierarchical_cluster | Fit a Hierarchical Cluster |
| jaccard_distance | Optimized Computation of Jaccard Distance |
| kmeans_cluster | Fit a Kmeans Cluster |
| nmf_cluster | Fit a Non-Negative Matrix Factorization Cluster |
| plot.hierarchical_cluster | Plots a hierarchical_cluster Object |
| presidential_debates_2012 | 2012 U.S. Presidential Debates |
| print.assign_cluster | Prints an assign_cluster Object |
| print.as_topic | Prints an as_topic Object |
| print.compare | Prints a compare Object. |
| print.data_store | Prints a data_store Object |
| print.get_documents | Prints a get_documents Object |
| print.get_terms | Prints a get_terms Object |
| skmeans_cluster | Fit a skmean Cluster |
| summary.assign_cluster | Summary of an assign_cluster Object |
| write_cluster_text | Write/Read Cluster Text for Human Categorization |
