My website can be found here: https://solomonmg.github.io
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Recent Posts
- Response to FiveThirtyEight’s Podcast about our paper, “Projecting confidence”
- Replication of Study 2 in Bias in the Flesh: Skin Complexion and Stereotype Consistency in Political Campaigns
- Exposure to Ideologically Diverse News and Opinion, Future Research
- When to Use Stacked Barcharts?
- Visualization Series: Using Scatterplots and Models to Understand the Diamond Market
- Streamline Your Mechanical Turk Workflow with MTurkR
- Generating Labels for Supervised Text Classification using CAT and R
- Working with Bipartite/Affiliation Network Data in R
- Visualization series: Insight from Cleveland and Tufte on plotting numeric data by groups
- Putting it all together: concise code to make dotplots with weighted bootstrapped standard errors
- Map the distribution of your sample by geolocating ip addresses or zip codes
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Solomon Messing 
I enjoyed working through your affiliation data webpage at
http://www.web.stanford.edu/~messing/Affiliation%20Data.html
Don’t you also have to redo “V(magallg)$degree = degree(magallg)” for magallggt1 in order to get the final graph? I didn’t see that line included.
Thanks.
Thanks John. I’d look at the updated version of that post (https://solomonmessing.wordpress.com/2012/09/30/working-with-bipartiteaffiliation-network-data-in-r/) rather than the old page.
Hi Solomon,
I have 2 questions:
1. Will Data Analysis discuss Bayes theorem?
2. This second question is a little longer. First some background. I
collect weed species data in the field for the Washington state dept
of natural resources(DNR). There are several Android apps for
identifying weeds by looking at photos but none that I can find by
comparing a photo that I take with my Android phone with a
downloadable database of known weed species. What I’d like to do is
write an app that downloads DNR’s weed photos of which there are about
1200 to my phone, find a weed in the field, take a photo and compare
it with DNR’s photos to see if there is a match.
Does this sound feasible? I want to keep it simple, not try to
identify every weed in existence, just here in Washington.
Best Regards,
Richard
PS: I tried going through the Discussion Forum but didn’t get a response.
Hi Richard, I’m not sure what you’re referring to the first part of your question, but for your second, take a look at caffe (http://caffe.berkeleyvision.org/) which provides some libraries to train image classifiers. What you’re proposing sounds like it will require a large set of images for training so I’d recommend thinking about incorporating crowd-sourcing to come up with a large and reliable training set.