Tutorials

Continuing on from Part 1, I build random forest models on the processed aptamer data with the goal of minimizing out-of-bag error rate, while also reducing the number of features from over a thousand to a more managable number. Boruta will allow us to do both for a 83% of molecules in the data.

In 2016, I gave a talk on the Boruta algorithm for feature selection. Unlike most feature selection procedures, Boruta aims to find all relevant features in a given dataset, meaning all features that provide some level of information. Boruta is particularly useful for the problem of aptamer selection in bioinformatics, which is quite difficult because of the highly unusual structure of the data, and because the processed data has more columns than rows.

With nothing more than latitude and longitude coordinates, you can get tons of public data and explore many interesting patterns.

Rush is one of the most prolific progressive rock bands in history. They started out as a hard rock band in the vein of Led Zeppelin, then moved into progressive rock, then added synthesizers in the 80s, and added hard rock again in the 90s and 00s. This makes them a great candidate for a musical analysis.