Tag Archives: r

Ranking algorithm for the layman – New Modeler Extension

There are a lot of ranking algorithms for you to use and represent your data. Now, that doesn’t mean that the ranking algorithm is the most appropriate for your situation. It all depends on what you are trying to accomplish and who will be the audience of your final product. Some ranking algorithms could be too sophisticated to be actually understood by a layman’s type of person. The reasoning to develop this particular piece of work was to not only rank specific type of datasets but be able to explain how the ranking is performed for the layman’s type of person.

main-view

The inspiration for creating this node came from this site -> http://www.psychstat.missouristate.edu/introbook/sbk14.htm. Now that this node exists, it allows us to reuse it over and over. According to the author of the site, transforming raw scores into percentile ranking, will enable us to: 1) Give us meaning and interpret the scores and 2) Provide a direct comparison between scores.

Sample Output:
results-after-ranking

If you want to learn more and try this extension go to the GitHub Repository. You can find my extension and all others in thePredictive Analytics Gallery.

Source: Missouri State – Score Transfromations

Source: | Ranking algorithm for the layman – New Modeler Extension

Installing rJava in RHEL

Installing rJava on Ubuntu is a piece of cake. All you have to do the code below, and boom!!! You got rJava working in R.

Now, the challenge was trying to get rJava working on RHEL. I could not find any proper documentation that worked. Instead, I ran into a bunch of posts and pointing to things that worked in their environment, but not on mine (so, this might not work on yours as well, but I hope it does). I usually like to give credit to the sources, but this time, they were so many over a long time span, that I could not remember what came from where anymore. So, I apologize for that. Below are the things that I did to get rJava working.

packages need

Once, you have installed the necessary packages; then it is time to

configure your environment

And that is it! If you got the install.packages(“rJava”) to work on R, that means that now you can call Java from within R console.