Structural Topic Models In R

Julia Silge has a great post on building Structural Topic Models in R using stm and tidytext:

The stm package has a summary() method for trained topic models like these that will print out some details to your screen, but I want to get back to a tidy data frame so I can use dplyr and ggplot2 for data manipulation and data visualization. I can use tidy() on the output of an stm model, and then I will get the probabilities that each word is generated from each topic.

I haven’t watched the video yet, but that’s on my to-do list for today.

Related Posts

Methods To Improve Model Accuracy

Tristan Robinson shows how to go back to the drawing board when your model’s accuracy isn’t cutting it: One of the reoccurring principles that appears with machine learning is that of Ockham’s razor, which states that the best models are simple models that fit the data well; this is not an irrefutable principle of logic, but […]

Read More

JupyterLab Now Available

Project Jupyter announces the general availability of JupyterLab: JupyterLab is an interactive development environment for working with notebooks, code and data. Most importantly, JupyterLab has full support for Jupyter notebooks. Additionally, JupyterLab enables you to use text editors, terminals, data file viewers, and other custom components side by side with notebooks in a tabbed work area. JupyterLab […]

Read More


January 2018
« Dec Feb »